Method and apparatus for selectively encoding and decoding a digital motion video signal at multiple resolution levels

ABSTRACT

At least one selected image of a digital video signal is encoded at multiple levels of resolution. For each level of resolution, a correction image is formed by subtracting the value of each pixel in a reference image of that resolution level from the value of each corresponding pixel in the selected image of that resolution level. The correction image is quantized and encoded. A decoder decodes the encoded quantized correction image for each resolution level. The value of each pixel in the decoded correction image having the lowest resolution is added to the value of each corresponding pixel of a reference image having the same resolution to form a result image of the lowest resolution. This result image is expanded to the next higher level of resolution. The value of each pixel in the expanded result image is added to the value of each corresponding pixel in the decoded correction image of the same resolution level to form a result image of that resolution level. This process is continued until each pixel value in the expanded result image, which has been expanded to full resolution, is added to the value of each corresponding pixel in the full resolution decoded correction image to form the final image which is stored in memory for subsequence display.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Continuation-In-Part of copending U.S. patentapplication Ser. No. 07/408,085, filed Sep. 15, 1989; which is acontinuation of U.S. patent application Ser. No. 07/104,457, filed Oct.5, 1987, now U.S. Pat. No. 4,868,653.

FIELD OF THE INVENTION

This invention relates to video signal processing generally andparticularly to systems for providing and decoding a compressed digitalvideo signal representative of a full color video signal.

BACKGROUND OF THE INVENTION

The need for compression to facilitate recording of a digital videosignal on relatively narrow-band media, such as a compact disc (CD), hasbeen recognized. In a system proposed by Takahashi et al. in U.S. Pat.No. 4,520,401, a digital video signal is encoded using differentialpulse code modulation (DPCM) for recording on a digital audio disc. Inthe known system, luminance (Y) and chrominance (R-Y, B-Y) components ofa video frame are separately compressed using DPCM. A circuit dividesthe components into picture element data groups of a specific number ofrows or columns which are adjacent on a screen. A header signal isprovided having a synchronizing signal, a picture mode identificationsignal and a picture information quantity identification code. Theheader signal is added to the beginning position of each of the dividedpicture element data groups to produce a digital video output signalhaving a signal format in which the digital luminance, the two kinds ofdigital color difference signal and the header signal are timesequentially multiplexed and recorded.

In an example of the Takahashi et al. system still frames of digitalvideo are recorded and updated at a rate of about four seconds perframe. The division of the compressed data into groups of lines witheach group containing complete color information provides apsuedo-motion effect in that the line groups may be sequentially updatedwhile displaying the previous frame thereby providing a partially movingpicture.

The system described in the parent application Ser. No. 07/408,085 isdirected to meeting the need for providing a compressed digital videosignal representative of a full motion color video signal, which issuitable for recording or transmission using relatively narrow bandmedia; and for decoding such a compressed signal to enable display offull motion video images at normal video frame rates. Although thatsystem is effective for encoding and decoding most images, it wasdiscovered that the system had some difficulty with certain images suchas, for example, images containing a large amount of fast and/oruncoordinated motion; that is, motion which does not occur substantiallyuniformly in the same direction over relatively large portions of theimage. It was found that such images were difficult to encode since thelinear fill technique employed by the system was too gross an encodingmethod to be used with images containing substantial amounts ofuncoordinated moving detail. With such images, it is desirable to encodeeach individual pixel; however, the system disclosed in the parentapplication is often allowed only an average of one-half bit forencoding each pixel. Therefore, it is desirable to add a feature to thatsystem which will enable effective compression and decompression ofselected images such as those having a substantial amount of movingdetail.

SUMMARY OF THE INVENTION

The present invention is directed to meeting the need for a compressionsystem for providing a compressed digital video signal representative ofa full motion color video signal, which is suitable for recording ortransmission using relatively narrow band media and which may bedecompressed at speeds at least equal to conventional video frame rates.In a specific embodiment described herein over one-hour of recordingtime has been achieved for compact disc read only memory (CD-ROM)recording media for 30 frame-per-second full motion color digital videorecording.

In accordance with an aspect of the invention, the first and secondframes of a digital motion video signal are compressed using differentcompression methods and an output signal is formed including anidentification code signifying each compression method.

In accordance with another aspect of the invention, each frame of adigital video signal is divided to form a plurality of regions and eachregion is separately analyzed and encoded by a selected one of severalcompression procedures to providing an optimum coding specific to thecharacteristics of the region being coded.

In accordance with another aspect of the invention, a digital motionvideo signal is compressed using compression thresholds controlled as afunction of the number of bytes per frame and an estimate of thedecoding time per frame of the compressed signal.

In accordance with yet another aspect of the invention, a video frame issplit repeatedly to provide a plurality of regions to be individuallyencoded, and the split direction, vertical or horizontal, is determinedby a comparison of distributions of pixel parameters associated with theregions.

In accordance with a further aspect of the present invention, at leastone selected frame, also referred to as a selected image, of a digitalvideo signal is encoded at multiple levels of resolution. For each levelof resolution, a correction image is formed by subtracting the value ofeach pixel in a reference image of that resolution level from the valueof each corresponding pixel in the selected image of that resolutionlevel. The correction image is quantized and encoded. For each level ofresolution, a result image is formed by adding the value of each pixelin the quantized correction image for that resolution level to the valueof each corresponding pixel in the reference image having the sameresolution level. The reference image of the lowest resolution levelcomprises an array of pixels all having the same value. The referenceimage of a higher resolution level is formed by expanding the resultimage of the next lower resolution level to that higher resolutionlevel. A decoder decodes the encoded quantized correction image for eachresolution level. The value of each pixel in the decoded correctionimage having the lowest resolution is added to the value of eachcorresponding pixel of a reference image having the same resolution toform a result image of the lowest resolution. This result image isexpanded to the next higher level of resolution. The value of each pixelin the expanded result image is added to the value of each correspondingpixel in the decoded correction image of the same resolution level toform a result image of that resolution level. This process is continueduntil each pixel value in the expanded result image, which has beenexpanded to full resolution, is added to the value of each correspondingpixel in the full resolution decoded correction image to form the finalimage which is stored in memory for subsequent display.

BRIEF DESCRIPTION OF THE DRAWING

The foregoing and further features of the invention are shown in theaccompanying drawing in which like elements are denoted by likereference designators and in which:

FIG. 1 is a block diagram of a digital video interactive systemembodying the invention providing recording and reproduction offull-motion video, multi-channel digital audio and auxiliary (e.g.,interactive) data using a compact disc read-only memory (CD-ROM) as therecording media;

FIG. 2 is a block diagram of a digital video encoder used in a recordingportion of the system of FIG. 1;

FIGS. 3-9 are diagrams illustrating digital video signal formats atvarious stages of processing in the encoder of FIG. 2;

FIGS. 10-12 are diagrams illustrating two methods of processing"oversized" frames in the encoder of FIG. 2;

FIG. 13 is a block diagram of a formatter providing padding anddithering for use in the encoder of FIG. 2;

FIG. 14 is a block diagram of a pre-compression processor used in theencoder of FIG. 2

FIG. 15 is a block diagram illustrating details of a portion of theprocessor of FIG. 14;

FIG. 16 is a block diagram of a digital video compressor used in theencoder of FIG. 2, providing intra-frame and inter-frame region-specificcoding, quantization by region area and frame-segmented variable lengthcoding;

FIG. 17 is a flow chart illustrating operation of an intra-frame coderused in the compressor of FIG. 16 for compressing still video frames andthe first frame of a motion video sequence;

FIG. 18 is a region diagram illustrating image edge analysis used in thecompressor of FIG. 16;

FIG. 19 is a block diagram of a roughness estimator providing split/filldecisions for use in the compressor of FIG. 16;

FIGS. 20-23 are region diagrams illustrating bilinear absolute fillcoding used in the compressor of FIG. 16;

FIG. 24 is a region diagram illustrating measurement of boundary errors;

FIG. 25 is a block diagram of an audio compressor used in the encoder ofFIG. 2;

FIG. 26 is a diagram illustrating quad-tree regionalization;

FIG. 27 is a diagram illustrating binary tree regionalization of animage in the compressor of FIG. 16

FIGS. 28 and 29 are examples of split/fill coding diagrams for theregionalized image of FIG. 27;

FIGS. 30 and 31 are examples of "tree" code for the coding diagrams ofFIGS. 28 and 29, respectively;

FIGS. 32A-J are region diagrams illustrating edge distribution analysisfor determining a most favorable region split direction;

FIG. 33A is a flow chart for computer apparatus or determining a mostfavorable split direction in the compressor of FIG. 16 by analysis ofthe distribution of horizontal and vertical edges in a region;

FIG. 33B is a table listing of parameters for the apparatus of FIG. 33A;

FIGS. 34A and 34B are diagrams illustrating two forms of regionsplitting in the compressor of FIG. 16;

FIGS. 35A-35E are diagrams illustrating weighted median filtering in thecompressor of FIG. 16;

FIGS. 36A-36C are diagrams illustrating non-linear low-pass filteringfor use in the encoder of FIG. 16;

FIG. 37 is a diagram illustrating finding a most favorable splitdirection by polynomial fit comparisons;

FIG. 38 is a flow chart for computer apparatus implementing the splitdirection method of FIG. 37;

FIG. 39 is a flow chart illustrating operation of an inter-frame coderused in the compressor of FIG. 16 for coding the second frame and allsubsequent frames of a motion video sequence;

FIG. 40 is a diagram illustrating region translation in the inter-framecoder of FIG. 39;

FIGS. 41 and 42 are vector and flow chart diagrams, respectively,illustrating selection of a best region search direction in theinter-frame coder of FIG. 39;

FIG. 43 is a diagram illustrating region translation and relative codingused in the inter-frame coder of FIG. 39;

FIG. 44 is a table illustrating region area dependent adaptivequantization used in the compressor of FIG. 16;

FIG. 45 is a flow chart illustrating operation of the apparatus in FIG.16 providing area dependent quantization of FIG. 44;

FIG. 46 is a block diagram of a stream segmented variable length coderfor use in the compressor of FIG. 16;

FIG. 47 is a diagram illustrating the format of data "streams" providedby the compressor of FIG. 16;

FIG. 48 is block diagram of a compressed digital video signal decoderused in the playback system 8 of FIG. 1;

FIGS. 49, 50 and 51 are examples of table listings of data stored in aregion location memory of the decoder of FIG. 48 for absolute, relative,dyad and DPCM coded regions of FIG. 48;

FIG. 52 is a block diagram illustrating a memory organization for use inthe decoder of FIG. 48;

FIG. 53 is a diagram illustrating relative region decoding of aninter-frame coded region by the decoder of FIG. 48;

FIG. 54 is a block diagram of apparatus providing the relative decodingof FIG. 53;

FIG. 55 is a diagram illustrating absolute region decoding in thedecoder of FIG. 48 of an intra-frame coded region;

FIG. 56 is block diagram of apparatus providing the absolute decoding ofFIG. 55;

FIG. 57 is a diagram illustrating DPCM decoding of a region in thedecoder of FIG. 48;

FIG. 58 is block diagram of apparatus providing the region DPCM decodingof FIG. 57;

FIG. 59 is a table listing of area dependent adaptive quantizationvalues for "dequantizing" pixel data in the decoder of FIG. 48;

FIG. 60 is a block diagram of apparatus for providing area dependentdequantization in the decoder of FIG. 48;

FIGS. 61 and 62 are diagrams illustrating dyad decoding in the decoderof FIG. 48; and

FIG. 63 is a block diagram of a dyad decoder for use in the decoder ofFIG. 48;

FIGS. 64A and 64B depict a block diagram of an encoding method forselected images in accordance with the present invention.

FIG. 65 depicts an example of a quantized correction image divided intonull and non-null regions.

FIG. 66 depicts a region table describing the regions of the exemplaryquantized correction image depicted in FIG. 65.

FIG. 67 is a block diagram of a decoding method for selected images inaccordance with the present invention.

DETAILED DESCRIPTION

The digital video interactive system of FIG. 1 comprises a recordingsystem 6 and a playback system 8. The recording system includes sources10, 12 and 14 which provide, respectively, a multi-channel sound signalS1, a color motion video signal S2 and an auxiliary data signal S3. Anencoder 16 encodes and combines signals S1, S2 and S3 to form a digitalrecording signal S4 (hereinafter, "bit-stream") that is recorded on acompact disc read-only memory (CD-ROM) disc 20 by means of a CD-ROMrecorder 18. Auxiliary data signal S3 may comprise interactive dataassociated with the video or audio signals or some other type of digitaldata which may be independent of the audio or video data.

The average data rate of the bit-stream S4 is controlled by a selectionof encoding parameters to equal the standard CD-ROM record/playbackbit-rate of about 1.2 mega-bits per second. The parameters are selected,as will be explained, so as to enable recording of up to one hour offull-motion digitally encoded color video, multi-channel digital audioand auxiliary data on CD-ROM disc 20.

The encoding of the digital full-motion color video portion of therecording signal to meet the relatively low channel capacity of theCD-ROM disc player requires very substantial data reduction. In aspecific example to be described, this data reduction is on the order ofabout 150:1 for an exemplary video frame rate of 30 FPS (frames persecond). To meet this critical requirement, while avoiding visible"artifacts" associated with conventional video compression techniques,encoder 16 converts the video signal S2 to a color frame sequentialcomponent form and separately subjects each frame of each component to anumber of specially adapted processes as will be described. Brieflylisted, these include variable sub-sampling, variable inter-frame andintra-frame compression employing what will herein be termed"region-specific" encoding, area dependent adaptive quantization,"segmented" variable length coding, reverse frame sequence reformatting,padding and frame dithering.

The selection of the individual processes, the selection of the share ofdata reduction provided by each and the selection of variablecompression parameters (e.g., thresholds, operating modes and,particularly, when to quit compressing) represents critical choices inmeeting the objective of encoding full motion color video for storage onCD-ROM digital audio tape (DAT) or other bandwidth limited media. Suchchoices depend on more than merely the channel capacity of the CD-ROMmedia. They depend as well on variables such as the video frame rate,the desired spatial resolution, certain specific characteristics of thevideo image content and on parameters of the decoder that is ultimatelyused for reconstituting the image. As will be explained, each individualvideo frame is converted to a component form and each component isdivided to form a number of regions of picture elements ("pixels") orblocks of pixels. Each region is then individually "custom" encoded.This process is hereafter referred to as "region-specific" coding. Thecoding for each region is selected from a group of codes to enable thevideo decoder in playback system 8 to meet the strict requirement ofcompleting all decoding tasks assigned to it in "real time", that is,within one video frame interval (a variable).

The foregoing and other aspects of recording system 6 are discussed indetail with reference to FIGS. 2-47, 61, 62 and 64-66. Details ofplayback system 8 are discussed later with reference to FIGS. 48-63 and67.

Encoder 16, in FIG. 2, includes input terminals 202, 204 and 206 forreceiving audio signal S1 from source 10, video signal S2 from source 12and auxiliary data signal S3 from source 14, respectively. As anoverview of the audio processing, signal S1 is subjected to channelselection and analog-to-digital (A/D) conversion, compressed withprovisions for preventing frame-to-frame propagation of errors andstored for later recovery as blocks of audio data to be included in eachvideo frame of bit stream S4 thereby providing audio/videosynchronization.

In detail, audio signal S1 is applied to a channel selector anddigital-to-analog (A/D) converter unit 208 which includes operatorcontrols (not shown) for selecting the number of channels to be encodedand the channel sampling rate. One channel is selected for monophonicrecording, two for stereo, four for stereo/bilingual, etc. The samplingrate currently used for high quality audio recording is 31.25 KHz whichsupports a 15 KHz audio bandwidth. The rate may be halved for standardquality or quartered for voice grade audio applications.

The data rate of the digitized audio signal S5 is reduced for recordingby means of an adaptive differential pulse code modulation (ADPCM)encoder 210 which encodes the sample-to-sample differences of signal S5to form a compressed digital audio signal S6. Since successive audiosamples are often highly correlated, fewer bits are required to encodethe sample differences. The term "adaptive" means that the encoder is ofa type that changes the bit significance of encoded differences as afunction of the previous encoded difference so as to provide fineresolution over a wide dynamic range.

Encoder 210 may be of conventional design but it is highly desirable forpurposes of overall audio/video coding that provision be made either tobypass or reset it on a periodic basis so as to periodically encode anaudio sample with full resolution. Illustratively, encoder 210 (FIG. 25)is reset once every 256 bytes. Recall that the audio signal isultimately organized in a block form with one block of audio dataincluded with each block of video data in bit stream S4. The formationof audio data "blocks" is supported via buffer store 212 which storessignal S6. Later the formatter 250 recovers the stored signal (S7)periodically on a frame-by-frame basis when the audio and video data arecombined as will be explained. Typical audio block sizes currently usedare 130 and 134 bytes for a video frame rate of 30 FPS and voice gradeaudio. The audio block size depends on the sampling rate, the number ofaudio channels to be recorded, and audio dithering within the formatter250.

One reason for periodically resetting or bypassing DPCM encoder 210 isto prevent audio errors, which may occur in the CD-ROM transmissionsystem, from propagating from frame-to-frame. This feature alsofacilitates subsequent editing of sequences to enable any frame to bechosen as an edit point. This feature is implemented as, shown in FIG.25 by means of a comparator 214 which supplies a reset signal to resetinput R of audio A DPCM encoder 21 when the byte count of the compressedaudio signal S6 (produced by a byte counter 216) exceeds the byte limitset by a byte limit source 218.

VIDEO CODING OVERVIEW

The principal elements providing video encoding in FIG. 2 comprise apre-compression processor 220, a digital video compressor 230 and anoutput signal formatter 250 which are described herein in detail withreference to FIGS. 3-47 and 64-66. As an overview, processor 220provides conversion of video signal S2 to a non-standard format thatprovides a variable amount of data reduction, facilitates subsequentcompression and contributes to certain features of the system relatingto variable frame-rate processing for controlling spatial-temporalresolution. Some images are converted at one frame rate for subsequentdisplay at an entirely different rate.

Compressor 230 employs, broadly speaking, four types of processing forreducing the quantity of digital data to encode a frame to a specific"optimum" value. This value is related to the CD-ROM channel capacitybut varies as a function of several variables including the frame rate,the desired spatial-temporal resolution, and other factors relating toerror propagation and visual appearance. The processing "types" includeintra-frame region-specific coding for still frames and for the firstframe and selected frames of a motion video sequence. Inter-frameregion-specific coding is used for the second and subsequent frames of amotion video sequence. Encoded frames are subjected to further datareduction by two processes in compressor 230 which will be referred toherein as "area dependent adaptive quantization" and "segmented streamvariable length coding". These processes are applied to each video frameto reach the desired "optimum" value noted above. Some sequences offrames may be repeatedly compressed with a change of compressionthresholds to reach the optimum compression value.

From time to time, an "impossible" frame may be encountered which ishopelessly oversized and can not be reduced to the desired byte count byaltering compression parameters without introducing noticeable visualartifacts. Such oversized frames receive special treatment in formatter250 which combines the audio, video, auxiliary (e.g., interactive) andother data to create the recording bit-stream signal S4. Specifically,formatter 250 analyzes frames backwards from the last frame to the firstand "borrows" space from short frames to hold the extra data of theoversized frames. Other functions provided by formatter 250 includeadding "padding" data to undersized frames and dithering the number ofbytes of data per frame to arrive at a specific average frame rateselected to keep the CD-ROM system operating at its maximum channelcapacity and to avoid pauses during playback. Pauses are avoided becausethe recovery time (the "seek mode latency") of a CD-ROM player can belengthy and unpredictable.

From time to time it may be desirable to select an image for specialtreatment in order to enhance the quality of the displayed video. Anexample of such an image is one which contains a substantial amount offast and/or uncoordinated motion; that is, motion which does not occursubstantially uniformly in the same direction over relatively largeportions of the image. This image, hereinafter referred to as a selectedimage, is encoded at multiple levels of resolution as will behereinafter described. Images may be selected based upon qualitativecriteria such as, for example, the visual quality of the decoded digitalmotion video signal. Images may also be selected based upon quantitativecriteria such as, for example when the mean square difference MSDexceeds a predetermined threshold value. Other quantitative criteriawhich are useable in selecting images for special treatment inaccordance with the present invention include, without limitation, whenthe peak value of the difference images exceeds a predeterminedthreshold value or when the mean absolute value of the difference imageexceeds a predetermined threshold.

Details of video processing are discussed in the following five sectionsentitled "Video Pre-Compression-Processing", "Video CompressionProcessing", "Post-Compression Processing", "Playback System", and"Video Decoding".

Video Pre-Compression Processing

Pre-compression processor 220 is coupled to input terminal 204 (in FIG.2) for converting the standard video signal S2 to a non-standard formspecially adapted for the particular types of compression and formattingfunctions subsequently employed in encoder 16. Specifically, each frameof the video S2 is converted in the "pre-compression" processor 220 toform three separate component frames comprising one luminance sub-frameand a pair of color-difference signal sub-frames. Each of thecolor-difference sub-frames is sub-sampled by a predetermined amountwith respect to the luminance sub-frame which, itself, may or may not besub-sampled with respect to the original video frame. The original videosignal may be analog or digital and may be of component form, compositeform or of another suitable form such as multiplexed analog component(MAC) form.

FIGS. 3, 4 and 5 illustrate the pre-compression processing of one frameof video signal S2 for the case where signal S2 is assumed to be an NTSCstandard composite video signal, one frame of which is shown in FIG. 3.FIG. 4 illustrates an intermediate stage of precompression processing inwhich the composite signal has been decoded to RGB component form,stripped of synchronizing and blanking intervals and digitized to formRGB picture element (pixel) arrays representing them "active" videoportion of each RGB field. The array dimensions, as illustrated, are 512pixels horizontally by 240 pixels vertically for each RGB component.

FIG. 5 illustrates the final stage of pre-compression processing inwhich the digital RGB arrays of FIG. 4 have been converted to form asingle luminance signal sub-frame (Y) measuring 256×240 pixels and twocolor difference signal sub-frames (I and Q) each measuring 64×60pixels. The three sub-frames are stored in a memory (to be described)for subsequent individualized "custom" compression. Comparing FIGS. 3, 4and 5 it is seen that one frame of signal S2 (FIG. 3) which requires737,280 bytes in digital RGB form (FIG. 4) is reduced to 69120 bytesafter sub-sampling, conversion and formatting (FIG. 5) thus providing aneffective data reduction for the frame of a factor of about 11:1 for theassumed rate of 30 FPS.

An operator control unit 222 is provided in FIG. 2 for varying the sizesof the sub-frames of FIG. 5 as a function of the frame rate tofacilitate varying the temporal and spatial resolution of encodedframes. This feature of the system relates to subsequent compression ofthe signals in the following way. The CD-ROM recording system cansupport a bit rate of about 1.2 mega-bits per second as previouslynoted. For 30 FPS (frame per second) video this channel capacitycorresponds to a video byte count (8-bits/byte) of 5125.12 bytes perframe. Of this, typically about 4500 bytes per frame are available forvideo with the remainder being used for audio and other data. The videocompressor (to be described) meets this requirement by compressing theformatted YIQ sub-frames by another factor of about 15:1 from 69120 tounder 4500 bytes per frame for the assumed rate of 30 FPS. If theplayback frame rate is halved then twice as much time (1/15th second) isavailable for decoding each frame and 9,000 bytes are available forencoding each frame. This increased decoding time and quantity of imagedata can be used in a variety of ways to provide improved image quality.One may for example, increase the number of pixels in the encoded frameor may more accurately encode the same number of pixels as at the higherframe rate (30 FPS).

FIG. 14 shows a specific implementation of precompression processor 220for providing the variable sub-sampling and format conversion functionspreviously described. Processor 220 comprises an RGB decoder 1402 whichconverts the composite video signal to RGB component form. The RGBcomponents are applied via anti-aliasing (2MHz) low-pass filters (1404,1406 and 1408) to inputs of a programmable graphics workstation 1410. Asuitable workstation is the "Adage 3000 Color Raster Display System".Operator control unit 222 of FIG. 2 comprises a terminal unit 222' (inFIG. 14) which supplies a "skip list" of fields, lines and pixels toworkstation 1410 as well as anti-alias filter coefficients and samplerate control data. Data reduced subframes of Y, I and Q samples areproduced by the work station and stored in a disc store 1412.

FIG. 15 is a block diagram illustrating the specific programmedconfiguration of workstation 1410 for use in processing video signal S2to create the non-standard sub-frame signal format of FIG. 5. Theanti-alias filtered analog RGB signals provided by filters 1404-1408 areapplied to respective analog-to-digital converters 1502-1506 whichdigitize the signals at a rate selected to provide 512 pixels per activeline interval as controlled by terminal 222' coupled to the workstationtiming and control unit 1530. The digitized RGB signals (FIG. 4) aresub-sampled by two banks of switches 1510 and 1514. Switches 1510 aretimed by unit 1530 to skip alternate fields of the RGB signals. Switches1514 skip alternate pixels, so that the resultant digitized andsub-sampled RGB signals each comprise arrays of 256×240 pixels perframe.

A matrix 1516 converts the sub-sampled RGB signals to YIQ form. The Iand Q color difference signals are each sub-sampled 4:1 both verticallyand horizontally with respect to the luminance signal Y. This isprovided by horizontal anti-alias low-pass filters 1518 (500 KHz),vertical anti-alias low-pass filters 1520 (60 lines/picture height),switches 1522 which skip 3 of 4 lines and switches 1524 which skip 3 of4 pixels. The formatted Y, I and Q sub-frame signals (FIG. 5) are thenstored in respective sub-frame locations in the disc store (e.g., a harddisc drive) 1412 for subsequent recovery and compression.

As previously explained, the filtering and sub-sampling parameters arevariables which depend on the frame rate. For the specific examples ofFIGS. 14 and 15 the frame rate is assumed to be 30 FPS. At differentframe rates the operator inputs appropriate anti-alias filtercoefficients, skip lists and conversion frequencies to timing andcontrol unit 1530 via terminal 222'. At any frame rate or resolution,however, it is important that the original signal, of whatever form(analog or digital, component, composite or MAC), be converted as shownin FIG. 5 to a form comprising a luminance component Y and a pair ofcolor-difference components that are filtered and sub-sampled bothvertically and horizontally with respect to the luminance component.Color difference components I and Q are used as examples herein.Alternatively, the color components may be of other forms, such as R-Yand B-Y or U and V.

In the preferred embodiment of the present invention, which additionallyemploys multi-resolution encoding of selected images, pre-compressionprocessor 220 of FIG. 14 is modified for processing a video input signalof MAC format by replacing RGB decoder 1408 with a MAC decoder providingYUV line sequential to YUV line parallel outputs, deleting the RGB/YIQmatrix in FIG. 15 and changing the sub-sampling parameters as needed toarrive at the individual (separated) sub-frames of luminance andcolor-difference components of FIG. 5. It will be appreciated that othervariations are possible. For example, the source may be decoded to YIQor YUV component form prior to filtering. Sampling may be done on eitherRGB or YIQ.

Video Compression Processing

After pre-compression processing the Y, I and Q video sub-frames arerecovered one at a time from disc store 1412 for independentcompression. The sequential recovery of sub-frames is indicatedsymbolically in FIG. 2 by sub-frame selector switch 224. In the positionshown, switch 224 applies all Y sub-frames of a motion video sequence tocompressor 230 which compresses and stores the complete sub-frames in abuffer store 232. Switch 224 is then advanced and the compressionprocess is repeated for all of the I sub-frames of the sequence.Finally, compression is applied to all of the Q sub-frames of thesequence thereby completing an initial stage of compression of asequence of color frames. Alternatively, switch 224 may be advanced toselect the Y, I and Q sub-frames of one complete frame of the sequencefor compression before advancing to the next frame of a sequence.

The compressed signal S9, as shown in FIG. 7, includes the threeindividually compressed sub-frames, each of which consists of abitstream header (H) followed by the compressed data for the sub-frame(Y, I, or Q). The header identifies which sub-frame the data correspondsto, the size (number of pixels horizontally and vertically) of thesub-frame, a checksum for diagnostic purposes, and various tables usedby the decoder. Further details of the format of signal S9 are discussedlater with reference to FIGS. 46 and 47. The compressed data of FIG. 7will hereafter be referred to as a video data "stream".

The feature of compressor 230 of individually compressing the YIQsub-frames to form the compressed digital video "stream" S9 greatlyenhances the compression efficiency. One reason is that even though thesub-frames represent the same image, they can differ from one-anotherdramatically because they represent different color measures of theimage. Some images, for example, may contain no flesh tones. Others maycontain no blue-green tones. Others may contain no color at all. Afurther reason for individual sub-frame compression relates to thestatistical distribution of codes representing the image. Variablelength coding is employed as one compression step. Variable length codesare selected in accordance with the frequency distribution or statisticsof data to be coded. Since the statistics of Y, I and Q encodedsub-frames differ, individual variable length codes are employed thatare optimized for each sub-frame. There are, in fact a number ofseparate statistical codes for each sub-frame as will be discussed.

After compression, the compressed video streams (S10) are recovered frombuffer store 232 and applied to a byte count monitor 234 and to a decodetime monitor 236 which identify, respectively, the number of data bytesand the decoding time for each individual frame of a video sequence.Since audio and auxiliary data will be added to each frame, the averagebyte count should be less than the total number of bytes allowed perframe in the bit stream S4. For encoding a video signal for playback at30 FPS from a CD-ROM, the average number of bytes available per frame is5125.12. This is determined by dividing the CD-ROM channel capacity bythe video frame rate. Monitor 234 provides an accumulated average bytecount over a sequence of video frames (alternatively monitor 234 may bearranged to count bytes on a frame-by-frame basis). This count is usedfor setting compression thresholds in a compression threshold controlunit 238 to maintain the average byte count of signal S10 below 4500bytes per frame. This allows room in the frame for audio and other datathat is later added. Dashed lines are used to signify this closed loopprocedure which is presently performed manually in a currentimplementation of encoder 16.

As previously noted, oversized video frames that can not be reduced to4500 bytes are accounted for during reformatting by borrowing space froman earlier frame. The mechanics of this are discussed later, in thesection on video post compression. Decode time monitor 236 measures thetime it takes to decompress each sub-frame of the compressed digitalvideo signal S10. This measurement may be accomplished by applying thesignal S10 to a decoder such as processor 30 of the playback system 8and measuring the processor decode time. For an exemplary playback rateof 30 FPS, the decode time of a frame should be no more than 1/30th of asecond. When this monitor detects a larger decode time, thresholds inthe threshold control 238 are adjusted to reduce the decode time of the"oversized" frame.

Alternatively, threshold 238 can be adjusted to merely keep the runningaverage of the decode time below 1/30th of a second. With such astrategy, there is no need to repeat a compression, even if it exceedsthe allowed decode time. In other words, the average can still beacceptable even if individual frames are not. As will be describedsubsequently, the playback system can cope with such temporary excessesin the decode time, without any effect on the playback rate, by using atechnique of borrowing decode time from "short" frames (i.e., thoseframes that require less than 1/30th of a second to decode). Thisalternative technique of coding "oversized" frames applies where theaverage decode time is less than 1/30th of a second, and the playbacksystem has adequate buffer storage. The amount of buffer storage neededby the playback system is monitored within the formatter 250 (FIG. 2),and if it is excessive, the threshold control is adjusted to reduce thedecode time further. This alternative strategy for using the decode timemonitor is desirable, because it permits a more accurate encoding ofthose frames that need a long decode time.

The decode time monitor may alternatively comprise an estimator, basedon the known decoding time characteristics of the video processor 30. Acareful examination of the decode process will reveal that it consistsof a fixed number of well defined operations (say "A", "B", etc.) eachof which requires a maximum length of time to complete. The encoder hasavailable to it the precise bit stream that will be processed by thedecoder. Hence the encoder can determine precisely how many times eachof these operations will be performed for each sub-frame. The decodetime estimate, T, is simply the sum of products: ##EQU1##

In the summation, each term "A_(i) " represents the total number oftimes a particular decoding action is performed. The term K_(i)represents the maximum decoding time of the action. Examples of suchactions include relative, absolute, DPCM, dyad and quad decoding.Moreover, each decoding action may comprise several actions depending onwhere the pixel is in the region being decoded. To facilitate the use ofsuch an estimator, the digital video compressor 230 stores the A_(i)counts associated with each sub-frame in the buffer-store 232. They areretrieved by means of a connection (not shown) from monitors 234 and 236to store 232. As an example of the use of equation 1 for estimatingdecoding time, the products that may be summed are (1) the number ofregions described by respective fill data times respective firstconstants, (2) the number of pixels included in each type of regiontimes respective second constants and (3) the number of rows of pixelsincluded in respective types of regions times respective thirdconstants. A constant term may be added to the sum of products toaccount for decoding steps common to all regions to be decoded.

FIG. 16 is a simplified block diagram of digital video compressor 230which includes an input terminal 1602 for receiving the YIQ selectedsub-frame signal S8 from switch 224 and another input 1604 for receivingthe threshold control signal S11 from control 238. Mode switch 240 ofFIG. 2 is indicated symbolically as switch 240' in FIG. 16. In theposition shown (UP), mode switch 240' applies the video sub-frame signalS8 to an intra-frame region-specific coder 1610 which producesregion-specific coded signal S12 that is applied via mode switch 240' toan area dependent adaptive quantizer 1630. The quantized region codedsignal S14 is applied to a stream-segmented variable length coder 1640as the final compression step in producing the compressed signal S9 forstorage in buffer 232 (FIG. 2). Reversing the position of switch 240'applies the video input signal S8 to an inter-frame region-specificcoder 1620 and selects the inter-frame coded signal S13 forquantization. Both encoders 1610 and 1620 are coupled to receive thethreshold control signal S11.

In operation, mode switch 240' is placed in the UP position for encodingstill frames and the first frame and selected frames of a motion videosequence using intra-frame coder 1610. Briefly stated, coder 1610 splitsthe frame into a number of small groups of similar pixels referred toherein as "regions". For each region a code is produced for representingthe values of all pixels of the region. This technique provides verysubstantial data reduction (compression) because very few bytes of codeare needed to specify where a region is, how big it is and what "fill"values are to be used to represent the region pixels. Further, thespecific coding method used for each region is optimally chosen based ondetailed characteristics of each region. This technique (herein,"region-specific" coding) of tailoring the encoding strategy, not justto individual images, but actually to individual regions within animage, greatly increases the amount of compression possible. Details of(1) how to find the regions, (2) how to code or "fill" the region (3)how to identify "good" and "bad" fill values and (4) what to do about"bad" fills are shown and described with reference to FIGS. 17-38, 65and 66.

Switch 240, is placed in the down position for encoding the second frameand all subsequent, non-selected frames of a motion video sequence usinginter-frame coder 1620. This different coding mode is used because oncethe first frame is encoded by coder 1610, the second and later framescan be coded on a "relative" basis using differences of the regions fromframe-to-frame. One advantage of this "relative" coding of regiondifferences is that smaller numbers are produced and smaller numbers canbe represented using fewer bits by means of variable length coding inwhich shorter codes are assigned to smaller numbers. Details of (1) howto find the best direction to look for corresponding regions in aprevious frame, (2) how to encode the region if found and (3) what to doif a corresponding region does not exist are discussed with reference toFIGS. 39-43 and 61, 62.

The region-specific coded signals S12 and S13 are subjected to what istermed herein as "area dependent" adaptive quantization in quantizer1630 which provides further data reduction. Recall that frames are codeda regions of pixels. The size of each region varies with details of theoverall image. For example, in areas of high detail there will be manysmall regions of a few pixels each. Conversely, in areas of low detailthere will be a smaller number of regions but these regions will containtens or even hundreds of pixels each. Quantizer 1630 achieves datareduction by variably quantizing region data as a function of the regionarea (i.e., the number of pixels in the region) such that small regionsare more coarsely quantized (and thus require fewer bits) than largerregions. This process, and the psycho-visual effect that makes thequantization essentially invisible, will be discussed with reference toFIGS. 44 and 45.

The quantized region-specific coded signal S14 receives additional datareduction (compression) in variable length coder 1640. Briefly, the datadescribing an image is rather complex. It includes data describing howthe regions were split and filled, how regions were shifted, parametersdescribing the fill values in terms of bi-linear polynomial coefficientsand further data in DPCM, dyad and quad coded form. The point is thateach video stream includes many types of data. These different types ofdata are formatted to occur in separate "segments" of each video stream.Coder 1640 determines the statistical occurrence of data for eachindividual segment of a video stream and assigns the shortest code tothe most frequently occurring data within each segment. This is doneindependently for each one of the Y, I and Q sub-frames comprising astream. In a preferred application, the different forms ofregion-specific codes are biased, so to speak, towards zero so thatsmall numbers have a higher frequency of occurrence than larger numbersand thus are assigned shorter variable length codes by coder 1640.Details of the foregoing "stream segmented" variable length coding aredescribed with reference to FIGS. 46 and 47.

Compressor 230 of FIG. 16 has been implemented by programming a digitalcomputer as described with reference to FIGS. 17-47. For the computer, amodel VAX 11/785 manufactured by Digital Equipment Corporation wasselected. Compression speeds of a few minutes per frame have beenachieved for typical motion video sequences. The principal goal ofcompressor 230 is not speed but rather is high quality for the imagesthat are ultimately displayed. This goal is achieved in large partthrough the use of what is herein termed "region-specific" coding aswill now be described.

Region specific coding comprises two actions, namely, (1) dividing theimage into several regions ("regionalization"), and (2) selecting"optimal" fill parameters for each region. These two actions areperformed concurrently, as will be described with reference to FIG. 17.

FIGS. 27-31 provide an overview of the regionalization process calledbinary tree decomposition. In this simplified example, the region 2702consists of four subregions (2704, 2706, 2708, 2710) in which the pixelsare assumed to have uniform gray levels (e.g., 141, 112, 90 and 98 outof a possible range of 256 gray levels). The pixel value distribution ofthis sub-frame is atypical, and is only intended to illustrate howbinary tree regionalization is applied, and how the resultingdecomposition can be efficiently encoded. In the more general case, the"fill" (i.e., the code representing the region pixel values) isdescribed by the linear expression Ax+By+C, where the coefficient "A"represents the slope or brightness gradient in the horizontal (X)direction, "B" represents the gradient in the vertical (Y) direction and"C" represents a constant or uniform level of brightness over theregion. In the example of FIG. 27, the terms A and B of the fillpolynomial Ax+By+C are both zero.

Binary tree decomposition is performed by splitting a region in half,then possible splitting each of the resulting sub-regions in half, untilthe resulting sub-regions can be efficiently encoded. Later, in thediscussion of FIG. 17, a number of strategies are described for decidingwhen a sub-region should be split, and in which direction would besplit, horizontal or vertical. For FIG. 27, these decisions are easy.The first split, labeled split 1 in FIG. 27 splits the regionhorizontally into two equal halves. The top half 2704 can be efficientlyencoded by the single value 141, while bottom half needs furtherdecomposition. A further vertical split, split 2 divides the remainingarea in half. The right half (2706) can be efficiently encoded by thevalue 112 and hence is not split any further. The left half, however,requires a further horizontal split, into two subregions 2708 and 2710which can be efficiently encoded by the values 90 and 98.

Other regionalization strategies are possible. For example in quad-treedecomposition, instead of picking a single split direction, both splitdirections are used together. This leads to a regionalization as shownin FIG. 26 where region 2602 is split to from four more regions2604-2608 one of which (2608) is further split to form four regions.Binary tree regionalization is the preferred mode because it has beenfound to normally result in fewer regions and hence fewer bits and lessdecode time.

FIGS. 28 and 30 illustrate the encoding of the absolute fill values andregion locations of the example of FIG. 27. The term "absolute" as usedherein signifies fill values obtained solely from the region data of theregion being coded. The term "relative" as used herein signifies regionfill values based upon frame-to-frame region differences. The invertedtree=like structure of the coding diagram 2802 in FIG. 28 representssuccessive divisions of region 2702 and is called a "binary tree"because each branch is split to form two branches. The top node of thetree represents the whole image. Each time a region is split, two newnode values are formed. Terminal nodes of the tree are encoded with theregion fill values.

The code (FIG. 30) to describe the complete tree consists, therefore, oftwo types of data: "values," which are the fill values, and "actions,"which are the split or fill commands. The "actions" and "values" areencoded using the same code "space". That is, they each comprisevariable-length- encoded non-negative numbers. It is always possible,however, to distinguish between an action and a value based on context,that is, the position of the action or value in the code sequence. Forinstance, in the example of FIG. 28, when a "fill" action isencountered, the next number must be a value. The next item after thisvalue must be another action, etc.

In more detail, the tree description data is ordered using the followingrule. For each node that is split, all the data pertaining to the "top"node (if a horizontal split) or the "left" node (if a vertical split) islisted, followed by all the data for the other node. This is aninherently recursive procedure that begins with the root node of thetree and operates successively on nodes of the tree until all terminalnodes of the tree are reached. For the example tree in FIG. 28 thisyields the tree code shown in FIG. 30. This short code, together withthe dimensions of the original image, gives all the information oneneeds to specify the size and location of every region and the value ofevery pixel in the image 2702. The "H" and "V" symbols signifyhorizontal and vertical splits. The "F" symbol signifies a fill action.

FIG. 29 illustrates an alternative and preferred format for encoding thebinary tree data for the regions of FIG. 27. It differs from the methodof FIG. 28 in that the fill data is encoded as node differences ratherthan as the actual values of the end nodes. This requires calculation inthe decoder to recover the actual fill values but has an advantage inthat the encoded values are numerically smaller. Compare, for example,the values 141, 90, 98, 112 of FIG. 30 with the values -7, -37, 18, and8 of FIG. 31. Since the values are encoded using a variable-length code,this produces greater coding efficiency, since this weights thestatistics of the values more heavily towards small numbers.

The coding procedure which results in the binary tree illustrated inFIG. 29 is performed as follows. First, the encoding process whichdevelops the binary tree of FIG. 28 is performed. Next, pairs of fillvalues at terminal nodes from the same branch point are differenced andaveraged. The difference value is assigned to the branch point and isthe value which will subsequently be encoded in the tree description.The average value is also assigned to the branch point, but only for thepurpose of determining other nodal or branch values working backwards upthe tree. That is, the average values are averaged and differenced withabsolute or average values from a corresponding node on a parallelbranch. The difference value is assigned to the branch point as thevalue to be encoded, and the new average value is used to determine thenext difference and average value working hierarchically up the tree.Differences are determined by subtracting the left nodal or branch valuefrom the right nodal or branch value.

In the example illustrated the terminal nodal value 90 is subtractedfrom the terminal value 98 to produce the difference value +8 which isassigned to the branch point designated "split 3". The average of thenodal values (90+98)/2=94 is also applied to the branch point and shownin angle brackets. The average value 94 at the branch point "split 3" isdifferenced and averaged with the terminal nodal value 112 to generatethe difference +18 and average 103 which are assigned to the branchpoint designated "split 2". This process is carried out all the way upthe tree until the firstmost branch point is reached.

A further encoding efficiency is accomplished at the top node of thetree by referencing the top node to the value 128. That is, the value128 is subtracted from the average value established for the top node.In this example, the average value for the top node or branch is 122.Subtracting 128 from 122 yields a value of -6. This value is assignedthe first position in the encoded tree description.

The tree description is illustrated in line "A" FIG. 31 and includes inorder of occurrence the value -6 followed by the direction "H" of thefirst split, followed by the difference value assigned the first branch,followed by the instruction to fill the left branch, followed by thedirection "V" of the next split, followed by the difference valueassigned that branch point etc. This code contains the same number ofinstructions as FIG. 30 but has smaller numerical values.

For decoding, the average value of the first two nodes (141 and branchpoint "split 2") is calculated by adding -6 to +128 to yield 122 whichequals (R+L)/2 where R and L are the right and left node or averagevalues respectively. The difference value, -38, transmitted in the codeis equal to (R-L) i.e., R-L=-37. But (R+L)/2=122. Solving theseequations simultaneously yields the left nodal value, L, equal to 141and the right branch average value R equal to 103. This process iscontinued down the tree. Occasionally, the averaging process describedabove may require dividing an odd number by 2. This may be dealt with byhaving the encoder and decoder agree on the same truncation or roundingstrategy.

The foregoing binary tree encoding methods require encoding negativenumbers. This is accomplished in the following way: A positive (or zero)number P is encoded by the positive number 2P, and a negative number Nis encoded by the positive number 2 N -1. Positive and negative numbersare differentiated because all positive values (2P) are even and allnegative values 2 N -1 are odd. This technique avoids placing a sign bitin the most significant bit position of fixed bitwidth codewords andtherefore eliminates extra bits between the sign bit and value bits forsmall values. When using this coding scheme, the tree code assumes thevalues in line "B" of code in FIG. 31.

As a further efficiency measure, it has been found useful to encode the"actions" and the "values" using different variable-length codes. Sincethere are only a few different actions, and many more possible values,their statistics are significantly different. Thus, using separatevariable-length codes produces some additional code savings.

The above description applies specifically to images containing absolutefills by constants. In actuality, there are five types of fillscurrently used, namely: absolute, relative, DPCM, dyad and quad. Each ofthese has its own separate action code. The node values discussed aboveonly apply to absolute fills. The fill values for the other four typesof fills are encoded separately in different code "segments" that arelater combined with the split/fill segment to form the overall videobit-stream. The use of many code segments is described in a subsequentdiscussion of "segmented stream variable length coding" and FIGS. 46 and47.

Vertical splits, V, and horizontal splits H, have approximately equalprobabilities of occurrence. An alternative way of encoding thisinformation has been found that uses fewer bits on average. It has beenfound that most splits tend to split the longer dimension (e.g., regions3402 and 3404 in FIG. 34A). Such a split is called a simple split and isencoded as S. If the dimensions of a region are equal and it is to besplit horizontally, it is coded as a simple split, S. This encoding isnot ambiguous to the decoder because the region dimensions are availableand if they are equal, the split code S is interpreted as a horizontalsplit. Any split which is not a "simple" split is called an alternatesplit and is encoded as A (e.g., regions 3406 and 3408 as shown in FIG.34B). Because of the greater probability of occurrence of simple splitsthe variable length encoder is able to use fewer bits on average byassigning a shorter code to represent simple splits. With this encodingstrategy, the tree of FIG. 29 would be encoded via line "C" of FIG. 31.While this approach does decrease the code size, it has the disadvantagethat the decoding time is increased by the need to deduce vertical andhorizontal split actions (V and H) from the simple and alternative splitcodes (S and A).

For images containing relative or dyad coded regions (described later),the region shift values (X_(o), Y_(o)) are also encoded in thesplit/fill tree description, using another action (called "shift")followed by the two shift values. As will be explained, a "shift" valueis a measure of the horizontal (X_(o)) and vertical (Y_(o)) offsetbetween a region of a given frame and a corresponding region of aprevious frame. The shift is a measure of frame-to-frame motion of aregion. These values are encoded in the tree description, rather thanseparately, for further efficiency of coding. Since many regions tend tohave the same X_(o), Y_(o) values, the "shift" action is defined to mean"apply these X_(o), Y_(o) values to this node and all child nodes ofthis node". Advantageously, this permits the shift values for regionshaving the same shift to only be encoded once.

FIG. 17 and FIGS. 18-38 related thereto provide the details ofintra-frame coder 1610 that encodes all "still" frames and the firstframe of a motion video sequence. FIG. 17 is a flow chart illustratingeach step in the encoding process provided by coder 1610. This"software" implementation of coder 1610 is presently preferred. However,it will be appreciated that the individual processing functions mayreadily be implemented by individual elements of apparatus providing thefunctions shown in the flow chart. Specific examples of such "hardware"implementations are included in FIGS. 18-38.

The first step for intra-frame coding (FIG. 17) comprises the START step(1702) and is initiated by placing mode switch 240' in the UP position(FIG. 16) for still frames or the first frame of a motion sequence.Simultaneously, switch 224 (FIG. 2) is placed to select the Y sub-frame.All of the Y sub-frames will be compressed before advancing switch 224to select the I and finally the Q sub-frames.

As a brief overview, FIG. 17 has four main actions. Prefiltering occursin step 1703. Sub-region stacking and selection is provided by steps1730, 1732, and 1704. This is the process (to be described) by which thesame strategy can be applied to every sub-region regardless of its size.Linear fill encoding, provided by steps 1706 to 1716, determines whethera region is suitable for encoding as a plane surface (Ax+By+C), and ifso, what the details of the encoding should be. DPCM encoding, providedby 1722 and 1724, are used for regions that are not suitable for linearfill encoding. Step 1720 performs post-processing on the resultingencoding to further reduce code size and decode time. Processingprovided by steps 1734 and 1736 check for the end of the sequence ofstill frames or the end of the first frame of a motion sequence.

The first action in FIG. 17 is to apply filter 1703 to the "image" ofvideo signal S8. Filtering removes extraneous detail which improves thespeed of the compression process, it decreases code size, and decreasesthe decode time because larger regions tend to be produced. Since simplelow pass filters also tend to blur the image, nonlinear filters arepreferred that remove low amplitude noise but preserve high amplitudeinformation. There are many kinds of filters that can be used for thispurpose, a preferred form being a cascade connection of a weightedmedian filter and a modified linear low pass filter. The modification isdescribed subsequently in reference to FIG. 36.

FIGS. 35A-E illustrate the weighted median filter. FIG. 35A illustratesa pixel 3502 to be filtered and its eight nearest neighbors. FIG. 35Bshows an array 3504 of weighting factors for filtering pixel 3502 toproduce the weighted value (12) for this one pixel 3506 indicated inFIG. 35C. The weighting method is shown in FIG. 35D. First, the valuesof pixel 3502 and of its eight neighbors are listed in ascending order(3503). The un-weighted median is seem to have the value of "11" units.One half of the values are higher and one half are lower. The weightingvalues (3504) from FIG. 35B are listed beneath the ordered values 3503.They determine the number of times each value is repeated to form anordered list 3508. In the example, the four corner pixels (11, 9, 1, 17)have weights of unity and are listed once in list 3508. The center sidepixels (12, 5, 10, 13) have weights of 2 and so are listed twice in list3508. The central pixel (15) to be filtered has a weight of 5 and so islisted 5 times in list 3508. The weighted median value (12) is the valuetaken from list 3508 for which half the weighted values are less andhalf are greater. This value (12) is the filtered value of the centralpixel of the region 3503 as shown (3506) in FIG. 35C. The remainingpixels are determined the same way by applying the weighting array 3504to each pixel and its 8 near neighbors.

The weights of FIG. 35B were selected for purposes of illustration tokeep list 3508 reasonably short. Exemplary weights for an average sceneare listed in FIG. 35E which shows corner weighting of 2, mid-sideweighting of 4 and center pixel weighting of 13. One may vary theseweights to achieve controlled directional spatial detail redirectionwhile preserving edge transitions. One may, for example, change diagonalcontributions to the filtered value by changing the corner weights.Vertical and horizontal contributions are determined, respectively, bythe values of the top and bottom or the left and right weights.Accordingly, the weighted median, in addition to preserving edges due tobeing a median filter, can exhibit selective directional characteristicsdue to the weighting factors.

FIG. 36A illustrates a modified low-pass filter suitable for use in thefiltering step 1703 which removes unimportant detail while preservingedge transitions. The filter comprises the combination of a lineartransversal filter 3602 and a modifier 3620 (both outlined in phantom).Briefly, the modifier detects edges and generates a "damping factor D"which is used to selectively mix the low pass filter input and outputsignals as a function of the edge amplitude to thereby suppress smallchanges while preserving larger signal transitions. Filter 3602comprises a cascade connection of pixel delay elements 3604 and 3606which delay an input signal at input terminal 3608 by one and two pixelperiods. An adder 3610 produces a low pass filtered signal by forming aweighted sum of the input signal (weight=1/4), the pixel delayed signal(weight=1/2) and the two-pixel delayed signal (weight=1/4). Modifier3620 includes a subtractor 3622 which detects transitions by subtractingthe low pass filtered signal of adder 3610 from the unfiltered one-pixeldelayed input signal provided by delay 3604. The output of subtractor3622 is applied to a non-linear detector 3624 which producescomplementary control signals D and 1-D for controlling multipliers 3626and 3628, respectively, which multiply the filtered and un-filteredpixel delayed signals. An adder 3630 adds the multiplied signals toprovide an output signal at terminal 3632. Detector 3624 may be a ROMprogrammed to output the values D and (1-D) responsive to thedifferences from subtracter 3622 applied as addresses.

FIG. 36B illustrates the non-linear characteristic of detector 3624 forproducing control signal D (hereafter, the damping factor) and 1-D as afunction of the subtractor 3622 output (difference signal). For smalldifferences characteristic of small detail features of an image thefactor D is near unity. Accordingly, multiplier 3626 selects thefiltered signal of adder 3610 as the output. For larger transitions thevalue of D decreases and so signal 1-D increases causing multiplier 3628to select more of the unfiltered signal as the output. For very largetransitions (D near zero) filter 3602 is essentially bypassed therebyfaithfully preserving the full amplitude of large edges. This is furtherillustrated in FIG. 36C in which 3640 indicates the occurrence of a steptransition for the input pixels represented by open circles. Dashed line3642 illustrates the response of a conventional low pass filter which,as shown, tends to smooth both large and small pixel variations. Thesolid circles indicate the response of the modified filter of FIG. 36A.The damping factor D is low for pixels approaching and leaving thetransition zone whereby small pixel variation (detail) are filtered. Thedamping factor is low in the transition zone thereby bypassing thefilter and thus preserving the steep transition.

Returning now to FIG. 17, steps 1704, 1730 and 1732 select and listregions for subsequent analysis. This process has one of two possibleeffects. It may yield an encoding of the region via step 1716 or 1724,and hence removal of the region from further analysis. Or it may causethe current region to be split 1726, and both halves put on a list ofregions for further examination. Each split reduces the size of theregion. When the region gets small enough it encounters the test for aminimum size region, 1722. This test prevents unlimited splitting, andhence forces eventual encoding of every region.

Initially, the region selection step 1704 treats the entire imagesub-frame as one single region. During this processing, it is likelythat a split 1726-1732 will occur, resulting in two subregions that needto be processed. Boxes 1730 and 1732 "push" two regions onto a list ofregions waiting to be removed by 1704. By "push" it is meant that theregion identities (locations) are stored in the region list. The nexttime select region 1704 is used, the top region on the list is encodedas will be described. The order in which regions are processed isdetermined by the order in which they are placed on this list. For ahorizontal split (1732) the bottom half region and the top half regionare each added to the list and the top half is first to be encoded. Fora vertical split 1730 the right half region and the left half region areadded to the list with the left half region being first to be encoded.This orderly sequencing of how regions are examined is known to thevideo processor 30 (FIG. 1), and is used by it during decoding tointerpret the sequence of codes used to represent each image.

Linear fill encoding is provided by steps 1704-1716 as will now bedescribed. It will be recalled that region-specific coding gets itsstrength from the ability to choose optimal encoding strategies for eachindividual region. Linear fill encoding is tried first, since it candescribe a large region with very few bits. If linear fill encoding isnot possible, the region is split (1726) and linear fill encoding isagain tried for each sub-region. As we shall see, the number of bitsrequired to encode a region using linear fill techniques does notincrease as the size of the region increases, so it is an excellentencoding strategy for large regions. Only when the resulting subregionsfall below a minimum size (TEST 1722) is another encoding techniqueused.

A mean square error measure (MSE) is one method used to determinewhether or not linear fill encoding is acceptable (1714). Since thismeasure is an average over the entire region, there may be localizedportions of the regions where the deviation from a plane surface isquite large and visually apparent, yet the MSE may be acceptably low. Toavoid this problem a roughness estimator 1706 is applied to the regionbefore attempting linear fill coding (1710). If the region fails thistest (1708) and is not of a minimum size (test 1722), it is split(1726-1732) and the same processing is applied to the resultingsub-regions so formed.

Roughness of a region in this example is determined by detecting edgesin the region. FIG. 18 illustrates a simple definition of edges, basedon large changes in gray level between adjacent pixels. FIG. 19 is ablock diagram of apparatus providing edge detection.

In FIG. 18 a region 1802 is shown comprising four rows and four columnsof pixels. Luminance (Y) signal values are indicated for the 16 pixels.By definition, an edge exists between adjacent pixels whose valuesdiffer by more than a threshold value (input via threshold control 238).A typical threshold value may be 25 units for a Y signal quantized to8-bits (i.e., a 256 level scale from black to peak white). Using a levelof 10 brightness units as an exemplary edge threshold, it is seen thatthere are two vertical edges (V) and three horizontal edges (H) in FIG.18.

If region 1802 were "split" (i.e., divided) horizontally between rows 2and 3, the result would be two regions neither of which contains ahorizontal edge. Notice also that the pixels of rows 3 and 4 range onlyfrom 3 to 5 in brightness, which is less than the edge threshold. Thus,horizontal splitting of region 1802 provides two regions which have nohorizontal edges and one region (rows 3 and 4) which may be encoded witha "fill" value of "4" that fairly represents the Y signal value for alleight pixels. Rows 1 and 2, however, still contain vertical edges V. Bysplitting this region vertically between columns 2 and 3 two moreregions are formed and neither contains edges. The 4×4 region containingthe uniform pixels "23" can be filled with a single value. The 4×4region having pixel values 1, 3, 9 and 12 has no horizontal or verticaledges but is not "fillable" with a single value because of the presenceof a pronounced "gradient". Filling of such a region requires a planesurface fill via 1710.

The fill procedure begins at step 1710 by using the method of leastsquares to find the coefficients A, B and C of the bi-linear polynomial(Ax+By+C) estimate of the region pixel values. Boundary error and MSEerror measurements are made (1711) and tests 1712 and 1714 are performedto determine acceptability of the fill value.

If a linear fill is not acceptable, because of the results of any of thetests 1708, 1712 or 1714, then the next step is usually to split (1726)the region. However, the test at 1722 prevents splits if the region sizeis already small. This is done for two reasons. First, the code size forlinear fill encoding is nominally independent of the region area.However, once the region falls below some predetermined size, otherencoding methods require fewer bits. Second, there can be delays in thedecoder (FIG. 48) whenever a new region must be decoded. If the imagewere represented using a large number of relatively small regions, thesedelays can become sufficiently significant to interfere with therequirement that images be decoded at a rate such as 30 FPS.

When the minimum size test indicates a minimum sized region, 1724encodes the region in DPCM (Differential Pulse Code Modulation) format.In this encoding method, the difference between every pixel and its leftneighbor is transmitted. However, since it does not have a left neighborthe first pixel of each line of the region is transmitted as thedifference between itself and the pixel immediately above it. The firstpixel of the first line of the region (which has no pixel to its left orabove it) is transmitted as the difference between itself and a mid-grayvalue, namely 128. The resulting differences may be additionally datareduced by passing them through a nonlinear quantizer. For decodingpurposes, a table describing the nonlinear quantization levels may betransmitted to the decoder in the header part of the compressed videobit-stream.

A number of DPCM quantizers may be used. This is practical becauseregion-specific coding enables matching the coding technique to theindividual region. These quantizer tables differ in the dynamic range ofthe differences. The DPCM encoder 1724 examines the statistics of eachregion and decides which quantizer table is better suited to thatregion, and generates a code specifying which dequantizing table is tobe used in decoding it.

FIG. 19 shows apparatus for providing the roughness test. FIGS. 32 and33 which are described later, show apparatus for determining the splitdirection. In FIG. 19 the region data is stored in a memory 1902.Subtractors 1904 and 1906 subtract the region pixels by row and bycolumn, respectively. Threshold detectors 1908 and 1910 compare thedifferences of pixels with a threshold value Th (e.g., 10 is assumed) todetect the horizontal and vertical edges which, in turn, are counted bycounters 1912 and 1914 and stored in an edge memory 1916. The storededge data is applied to a zero detector 1920. A HIGH output of detector1920 signifies that there are no horizontal or vertical edges in theregion and initiates the process of finding a value (or values) to fillthe region. If edges are present, the edge data in memory 1916 isapplied to split logic circuit (FIG. 33A) for finding a split directionas described later.

Alternative definitions of roughness are also possible. For example, onecan estimate the slope between adjacent pixels by multipointinterpolation techniques. If the slope is larger than a threshold and isnot constant over the region, then the surface is rough.

Returning to FIG. 17, it will be assumed that test 1708 finds no edgespresent in the region. This initiates the process of finding a fillvalue for representing all pixels of the region as a group. This is donein step 1710 by generating coefficients A, B and C of a bilinearpolynomial (Ax+By+C) estimation of pixel values for the region using themethod of "least squares" estimation. The estimated pixel values arecompared with the actual values for all pixels of the region todetermine the closeness or "fit" of the estimate. The "fill" valuecomprises the coefficients A, B and C of the polynomial that satisfiestwo tests, namely, a "boundary error" test 1712 and a "mean squareerror" test 1714.

FIGS. 20-24 show in detail how the polynominal fill values are found andhow the two tests for acceptability of the fill are performed. FIG. 20represents the most elementary case where all pixels of region 2002 areof the same value (5 units). There is no brightness gradient in thehorizontal ("x") direction therefore the coefficient "A" which signifiesthe horizontal brightness gradient or "slope" equals zero. There is nobrightness gradient in the vertical direction either. Therefore, thecoefficient "B" representing vertical slope is also zero. The onlycoefficient remaining is "C", which is the polynominal coefficientrepresenting the constant or uniform signal level of 5 units. The codeto represent this simple case is shown as ABS 0 0 5 to signify what willbe called absolute coding hereinafter to distinguish region codes basedon the actual signal values from region codes based on frame-to-framedifferences (hereinafter relative codes). Decoding of region 2002comprises assigning a value of 5 to every pixel in the region.

In FIG. 21 the region 2102 includes a horizontal brightness gradient ofone unit per pixel in the x direction. Starting in the upper left handcorner the values are 4, 5 and 6. The fill polynomial Ax+By+C thereforehas coefficients A=1, B=0, C=4 (taking the upper left pixel as areference level). The code is therefore ABS 1 0 4. This is decoded byassigning a value 4 to the upper left hand pixel and adding a gradientcorrection to each horizontal pixel of one unit of brightness per pixel.Since there is no vertical gradient, successive rows are replicas of thefirst row. FIG. 22 is similar except that the gradient is verticalrather than horizontal.

In FIG. 23 the region 2302 has both horizontal and vertical gradients.Taking the upper left corner pixel as a reference, the polynomialconstant C equals 5, the brightness increases by 1 unit per pixel in thex direction and changes by -1 unit in the y direction. The code istherefore ABS 1 -1 5. Decoding is effected by assigning a value of 5 tothe first pixel and incrementing its value by one unit per pixelhorizontally. The second and third rows are similarly decoded afterdecrementing the starting pixel value by the vertical slope value (minusone pixel per column).

The above examples suggest that the slope values A and B in thepolynomial Ax+By+C are always integers. It has been found, however, thatmost slopes that occur in real images are not integers, and in fact areusually less than 1 in absolute value. The A and B values are,therefore, specified in units of 1/256ths; i.e., binary numbers with theleast significant 8 bits representing the fractional part of the slope.

In FIGS. 20-23 the polynomial coding is exact. That is, for theexemplary values given, it just happens that upon decoding the decodedregions will have exactly the same values as the original regions. Inpractice this ideal situation may not occur very often. For this reasonmeasures are needed to determine if the bi-linear polynomial fill valuesproduce a reasonably close replica of the actual pixels values when theregion is ultimately decoded. The tests used are the mean square error(MSE) and the boundary error test of the polynomial fit as illustratedin FIG. 24.

FIG. 24 illustrates a specific case where the polynomial fill is notexact and acceptability of the fit is tested. Region 2402 is a region ofpixel values as they appear in the image. Array 2404 is a correspondingset of values that is produced when using a polynomial of the formAx+By+C, the coefficients of which were determined using least squaresanalysis on the data of region 2402. Array 2404 shows a uniformhorizontal gradient of 1 and a uniform vertical gradient of 1. Array2406 is a set of values corresponding to the errors between the actualpixel values and the corresponding generated pixel values. The MSE isobtained by taking the square root of the average value of the squaresof the values in array 2406. For this specific example the MSE is 1.This value is compared with a threshold value to determine acceptance orrejection of the fill data.

The boundary error is based on analysis of the 12 pixels that constitutethe boundary of this region. It has been found that boundary errorsrequire tighter tolerances than errors interior to a region if falseedges are not to be generated between abutting regions. One possibleboundary test is to compare each of the boundary difference values inarray 2406 against a predetermined threshold value, e.g., 10, and if anyof the differences exceed this threshold, to reject the coefficients.

A preferred embodiment of the boundary test looks for coherence invalues. It has been discovered that boundary errors are more visiblewhen they are coherent; that is when adjacent pixels have errors withthe same sign. Random differences such as those along the top, bottomand left side of array 2406 are unlikely to produce a false edge in areproduced image. In the preferred embodiment, the boundary estimator1711 identifies contiguous blocks of boundary errors which have the samesign. Only boundary pixels that are part of a block whose length isgreater than a threshold (from threshold control 238), typically 2, maybe considered. For example, in array 2406 of FIG. 24, only the block oferror values having the value +1 on the right boundary would beconsidered, a boundary error estimator of "1" generated. The averageblock error value of such coherent pixels is compared against athreshold value. If the error exceeds the threshold value the fill isrejected.

In summary, tests at 1712 and 1714 are performed to see whether the fitrepresented by Ax+By+C should be accepted. The test at 1714 might failbecause the average deviation from a plane surface is too high. In otherwords, the MSE test essentially measures closeness of the fit of theencoded pixel values (Ax+By+C) to the actual pixel values. An MSEthreshold is selected and used as an input for threshold control 238,and is typically 4. The test at 1712 might fail if the errors along theboundary might tend to introduce a visible transition between adjacentregions when they are decoded and displayed. boundary threshold is alsoused as an input for threshold control 238 and is typically 20.

Returning to FIG. 17, once the decision has been made to split a region,the region is analyzed to find the best split direction. If test 1728indicates the need for a vertical split, step 1730 splits the regioninto a left half and right half region. If test 1728 indicates the needfor a horizontal split, step 1732 splits the region into a top half anda bottom half. If the split is horizontal, the compression process isrepeated starting with the next region selected (1704) being the upperone of the split regions. If the split is vertical, the compressionprocess is repeated selecting (step 1704) the left one of the splitregions. This process of splitting and compressing continues until allthe regions created by the splitting process are encoded (step 1705).Then remerge (step 1720 to be described) is done and the intra-framecompression operation ends (1736) for the Luminance (Y) signal subframe.A complete color frame is encoded by repeating the compression processfor the remaining I and Q sub-frames. If additional still frames are tobe encoded, the next frame is selected (1735) as a result of a "lastframe" test 1734 and the process repeats.

Finding a split direction for a region to be split (1726 of FIG. 17) maybe accomplished by means of: (1) edge distribution analysis; or (2)polynomial fit analysis. Each of these procedures, and specificapparatus for providing the split direction indication are described asfollows with reference to FIGS. 32-38.

Edge distribution analysis is used to find a most favorable splitdirection for cases where the reason for splitting the region is thepresence of edges in the region (e.g., failure of the roughness test1708 in FIG. 17). FIGS. 32A-J provide examples of regions to be splitusing edge distribution analysis. FIGS. 33A and B, discussed later, showhow the analysis may be implemented.

FIGS. 32A-E illustrate five cases where a vertical split is favored overa horizontal split. In FIG. 32A the region 3202 contains two verticaledges which lie on the vertical bisector of the region. Nothing would begained by splitting this region horizontally since each subregion wouldstill contain an edge whereas a vertical split will produce two regions(1, 3 and 2, 4) neither of which contains an edge. In FIG. 32B there areno edges in the right half of region 3204 therefore a vertical splitwill produce one sub-region having no edges. A vertical split issimilarly favored in region 3206 of FIG. 32C. In FIG. 32D there are manyvertical edges in region 3208. Although edge free regions will not beproduced here, a vertical split is favored since it is more likely thatan edge will be eliminated than if it were split horizontally. In FIG.32E region 3210 contains several horizontal and vertical edges with noclear advantage. For this case aspect ratio analysis is used.Specifically, region 3210 is wider than its height and a vertical splitis selected because it will tend to produce sub-regions that are moresquare. On average, this has been found to result in fewer regions beingproduced for typical images where the edge analysis shows no clearadvantage. Regions 3212-3220 of FIGS. 32F-J are split horizontally forreasons similar to those discussed with regard to vertical splitting ofregions 3202-3210.

From the foregoing it is seen that there are a number of factors whichhave a bearing on selection of a split direction. In practice, the splitdecision is not as simple a matter as it might appear from the examplesgiven because real images produce regions having many more edgedistributions than the relatively simple examples of FIGS. 32A-J. Theflow chart of FIG. 33A and associated table of FIG. 33B illustrate amethod for finding a split direction which takes into account thecomplex edge distributions encountered in splitting regions of typicalvideo images.

In FIG. 33A the split direction analysis starts (3302) with the step(3304) of detecting edges in four quadrants of the region to be split.As shown in FIGS. 32A and 32F, the quadrants are designated 1 for thetop left, 2 for the top right, 3 for the bottom left and four for thebottom right. Next (step 3306) four functions V13, V24, H12 and H34 argenerated as listed in the table of FIG. 33B. The function V13 equalsthe sum of a number of terms (Col. 1 of FIG. 33B) relating to edges inthe left half of the region (i.e., quadrants 1 and 3). The function V24is comprised of the sum of a number of edge distribution terms for theright half (quadrants 2 and 4) of the region. The function H12 and H34similarly relate to sums of terms for the top and bottom halves of theregion. Specific terms are discussed later.

At step 3308 multiplication is performed to produce what is hereintermed a vertical factor VF and a horizontal factor HF. The verticalfactor VF equals the product of the region height (H) times V13 timesV24. The horizontal factor HF equals the product of the region width (W)times H12 times H34. The factors HF and VF are compared at step 3310. Avertical split is made (3312) if VF is less than HF and the program ends(3316) otherwise the region is split horizontally (3314) and the programends.

In operation, any factor which tends to make VF smaller than HF favors avertical split. From step 3308, for example, if the edge analysisfactors V13 and V24 ar equal to H12 and H34 than a vertical split willbe favored if the region height H is less than its width. This conditioncorresponds to the example of FIG. 32E where it was seen that there wasno clear advantage shown by edge analysis but the aspect ratio testfavored a vertical split to obtain sub-regions that are more square.

The factors of FIG. 33B (calculated in generation step 3306) becomeimportant in cases where the vertical and horizontal edge distributionsare not uniform in a region. Factors tending to make V13 (left half) orV24 (right half) small favor a vertical split. For example, if thenumber V1 of vertical edges in quadrant 1 is equal to the number V3 ofvertical edges in quadrant 3, then the factor V1-V3 will be zero thusfavoring a vertical split. Vertical and horizontal edge differencefactors V1-V3, H1-H3, V2-V4, H2-H4 etc. are included for all quadrants.These terms are all squared in FIG. 33B to give them added weight. Theterms Ho and Vo represent the number of horizontal and vertical edges,respectively, which will be eliminated by the split (i.e., edges fallingon the split line). The elimination of edges has also been foundimportant and so these terms are also squared to increase their weightin the split direction test. The remaining factors H1, H2, V1, V2 etc.represent the number of edges per quadrant. If, for example, there aremany horizontal edges in the left and right halves a horizontal splitwill be favored (e.g., FIG. 32I). Other examples of the application ofthe table of FIG. 33B are apparent. For example, the terms may beweighted differently than shown. Also, the region may be more finelysubdivided and additional terms for split direction analysis added tothe table.

The foregoing assumed that the reason for a split was a YES exit fromthe roughness test 1708. If the reason for the split was a linear fillthat failed the MSE test (1714) or the boundary error test (1712), thena different method for choosing the split direction is appropriate.

FIG. 37 illustrates analysis of the polynomial fit to determine thesplit direction. Recall from FIG. 17 that a region will always be splitif either the mean square error (MSE) or the boundary error tests of thebi-linear polynomial Ax+By+C is unsatisfactory. In FIG. 37 the verticalportion (By+C) of the bi-linear polynomial is compared with the verticalLuminance values Y_(V) (i.e., the average luma values by row). Also, thehorizontal portion (Ax+C) is compared with the horizontal Luminancevalue Y_(H) (i.e., the average luma value by column). The comparisonproviding the better "fit" (i.e., lower MSE) is selected as the splitdirection.

A flow chart for a computer apparatus implementation of this method isshown in FIG. 38. Measurements of the fit of Ax+C to Y_(H) and By+C toY_(V) are made in steps 3802 and 3804. Test 3806 selects a verticalsplit 3810 if the vertical "fit" (i.e., MSE) is better than thehorizontal fit as shown in the example of FIG. 37. Otherwise test 3806selects a horizontal split 3808 and the program ends (done).

An advantage of this technique of finding a split direction is that itfrequently results in a "fillable" region if most of the error occurs inone-half of the region. In the example of FIG. 37 the vertical fit isgood and most of the error in the horizontal direction is on theright-hand side of the image. Thus, for this case a vertical split isfavored and the left side of region 3702 will probably not requirefurther splitting since the errors (horizontal) are mostly on theright-hand side.

Returning to FIG. 17, when all the regions have been encoded, theprocess continues at step 1720. Remerge examines the encoding generatedfor all regions of the image, and performs some post processing on it toremove some code and to improve the decoding time. If two adjacentregions of like size have been encoded with the same DPCM quantizingtable, the split could have been avoided. Remerge (step 1720) willmodify the coding stream to replace the two smaller regions by thelarger region. The rejoined two regions can thereafter participate in afurther rejoining operation with adjacent like sized DPCM encodedregions.

FIGS. 64-66 provide details of intra-frame decoder 1610 that encodesselected images. As previously stated, it may be desirable to selectcertain types of images, such as images which contain a large amount offast and/or uncoordinated motion for special treatment in order toenhance the quality of the displayed video. Such images, referred to asselected images, are encoded at multiple levels of resolution. For eachlevel of resolution, a correction image is formed by subtracting thevalue of each pixel in a reference image having that level of resolutionfrom the value of each corresponding pixel in the selected image of thatresolution level. The correction image of that resolution level is thenquantized and encoded.

Referring to FIG. 64A and 64B, there is shown a block diagram depictinga preferred embodiment of the selected image encoding method inaccordance with the present invention. The full resolution selectedimage, hereinafter referred to as the level 0 selected image 6402, isresolved into a selected image having a lower resolution, hereinafterreferred to as the level 1 selected image 6404. The level 1 selectedimage 6404 is resolved into a still lower resolution selected image,hereinafter referred to as the level 2 selected image 6406. The level 2selected image 6406 is resolved into yet a lower resolution selectedimage which, in a preferred embodiment, is the lowest resolutionselected image, hereinafter referred to as the level 3 selected image6408. In the preferred embodiment, the level 1 selected image 6404 hasapproximately 1/4 the number of pixels of the full resolution level 0selected image 6402; the level 2 selected image 6406 has approximately1/16 the number of pixels of the full resolution level 0 selected image6402; and the level 3 selected image 6408 has approximately 1/64 thenumber of pixels of the full resolution level 0 selected image 6402.Although in the preferred embodiment the selected image is resolved intothree lower resolution images, resolving the selected image into feweror more levels of resolution is also within the scope and contemplationof the present invention. Accordingly, the present invention encompassesresolving the selected image into at least one lower level ofresolution.

A level 3 correction image 6410 is formed by subtracting the value ofeach pixel in a level 3 reference image 6412 from the value of eachcorresponding pixel in the level 3 selected image 6408. The level 3reference image 6412 comprises an array of pixels all having the samevalue. In the preferred embodiment, the range of possible pixel valuesin the selected images 6402, 6404, 6406 and 6408 is from 0 to 255. It ispreferred that the value of the pixels in the level 3 reference image6412 be midpoint in the total pixel value range. Accordingly, each pixelof the level 3 reference image 6412 has a value of 128. As a result, thevalues of the pixels in the level 3 correction image, hereinafterreferred to as difference values D, are signed and range from -128 to+127. The difference value D of each pixel in the level 3 correctionimage 6410 is then quantized (6414) to form a level 3 quantizedcorrection image 6416. The level 3 quantized correction image 6416 isencoded (6418) as will be subsequently described.

Alternatively, a different constant value of the pixels in the referenceimage of lowest resolution may be chosen based upon the actual pixelvalues in the selected image, and that chosen value transmitted in thebitstream. For example, the average value of the actual pixel values inthe selected image may be chosen and transmitted in the bitstream.

A level 3 result image 6420 is formed by adding the value of each pixelin the level 3 quantized correction image 6416 to the value of eachcorresponding pixel in the level 3 reference image 6412. The level 3result image 6420 is expanded to form an expanded level 3 result image6422. The vacant pixel locations created by the expansion are filled bypixels whose values are preferably determined by linear interpolation.This is accomplished for example, by adding the values of the pixels oneither side of the vacant pixel location, dividing the resultant sum by2 then inserting the result in the location of the vacant pixel. Itshould be noted, however, that other methods of interpolation could beused and are considered to be within the scope of the present invention.For example, polynomial interpolation tends to reduce average sizes ofpixels in the correction image thereby decreasing the bit rate. In thepreferred embodiment, each lower level of resolution contains 1/4 thenumber of pixels of that of the higher resolution level. However, itshould be noted that the number of pixels in each lower resolution levelcould be reduced by a factor such as two, three, or five, includingnon-intergal ratios and such is considered within the scope of thepresent invention. In cases such as these, polynomial interpolation maybe especially useful.

A level 2 correction image 6426 is formed by subtracting the value ofeach pixel in a level 2 reference image which, in the preferredembodiment, is the expanded level 3 result image 6422, from the value ofeach corresponding pixel in the level 2 selected image 6406. Althoughthe value of each pixel in the level 2 correction image 6426, which isalso a signed difference value D could range from -255 to +255, it ispreferred that values outside the range of from -128 to +127 are clippedthereby limiting the difference values D to a range of from -128 to+127. The difference values D are quantized (6430) to form a level 2quantized correction image 6432. The level 2 quantized correction image6432 is encoded (6434) as will be subsequently described.

A level 2 result image 6436 is formed by algebraically adding the signeddifference value D of each pixel in the level 2 quantized correctionimage 6432 to the value of each corresponding pixel in the expandedlevel 3 result image 6422. The level 2 result image 6436 is expanded toform an expanded level 2 result image 6440. The vacant pixel locationsin the expanded level 2 result image array are filled as previouslydescribed with respect to the expansion of the level 3 result image6420. A level 1 correction image 6442 is formed by subtracting the valueof each pixel in a level 1 reference image which, in the preferredembodiment, is the expanded level 2 result image 6440, from the value ofeach corresponding pixel in the level 1 selected image 6404. The valueof each pixel in the level 1 correction image 6442, which is also asigned difference value D ranging, in the preferred embodiment, from-128 to +127, is quantized (6444) to form a level 1 quantized correctionimage 6446 which is then encoded (6448) as will be subsequentlydescribed.

A level 1 result image 6450 is formed by algebraically adding the signeddifference value D of each pixel in the level 1 quantized correctionimage 6446 to the value of each corresponding pixel in the expandedlevel 2 result image 6440. The level 1 result image 6450 is expanded toform an expanded level 1 result image 6454. The vacant pixel locationsin the expanded level 1 result image are filled as previously describedwith respect to the expansion of the level 3 result image 6420. A fullresolution level 0 correction image 6456 is formed by subtracting thevalue of each pixel in a full resolution level 0 reference image which,in the preferred embodiment, is the expanded level 1 result image 6454,from the value of each corresponding pixel in the level 0 selected image6402. The value of each pixel in the level 0 correction image 6456,which is also a signed difference value D ranging, in the preferredembodiment, from -128 to +127, is quantized (6458) to form a level 0quantized correction image 6460 which is encoded (6462) as will besubsequently described.

In the description of the preferred embodiment set forth above, thequantized correction image for each resolution level is based upon theexpanded result image of the next lower resolution level. However, thequantized correction image at a particular resolution level could bebased upon a result image expanded from a level which is two or morelevels of resolution lower and as such is considered within the scope ofthe present invention. For example, the level 3 result image could beexpanded to the level 1 resolution. The level 1 correction image wouldthen be formed by subtracting the value of each pixel in the expandedlevel 3 result image (which in this case is now the level 1 referenceimage) from the value of each corresponding pixel in the level 1selected image.

Although, in the description set forth above, a full resolutioncorrection image is formed, quantized and encoded, such processing ofthe image at full resolution may not be necessary or desirable toachieve a high quality result. Accordingly, in an alternative preferredembodiment of the present invention, the processing is performed atlevels of resolution lower than full resolution. For example, a level 1image is not formed and expanded to form a full resolution referenceimage. Nor is a level 0 correction image formed and quantized to form afull resolution quantized correction image to obtain a final image aswill be subsequently described. Also in this alternate preferredembodiment, the selected image may be resolved to only two levels ofresolution lower than full resolution. That is, the full resolutionlevel 09 selected image is only resolved into the level 1 selected image6404 and the level 2 selected image 6406. Consequently, level 2 is thelowest level of resolution in this embodiment. Accordingly, the level 2reference image comprises an array of pixels all having the same valueas previously described with respect to the level 3 reference image6412.

The quantized correction images of the different resolution levels areencoded as follows. The quantized correction image for each level isdivided into m×n pixel blocks which are grouped into null and non-nullregions. In the preferred embodiment m=8 and n=8. A null region is aregion in which all pixel values have been quantized to zero. In anon-null region, at least one pixel has a non-zero quantized value. Thenon-null regions are encoded using a code, type preferably a vectorquantization code type such as, for example, quad, dyad or DPCM. * Avector represents one or more pixel values, one being a special case.For example monads, dyads and quads represent vectors of one, two andfour pixels respectively. A vector can be applied directly, or couldemploy spacial prediction. For example, DPCM is used for monads, whereeach monad is predicted by the immediately preceding monad. In thiscontext, DPCM is considered to be a special case of a vectorquantization code type using monads.

It should be noted that the quantized correction image for each levelcould be divided into linear fill and non-null regions and such isconsidered within the scope of the present invention. Where the regionsare so divided, a null region could be considered a special case oflinear fill. It should be further noted that other techniques for stillimage encoding known in the art could be used; for example, the discretecosine transform (DCT) technique; and such is also considered to bewithin the scope of the present invention. In the preferred embodiment,the code type used is explicitly set forth in the bit stream.Accordingly, the decoder recognizes the code type used in connectionwith each level of resolution by reading a code in the bit stream. Thispermits any appropriate code type to be used in encoding any level ofresolution.

In the preferred embodiment, the quantized correction image having thelowest level of resolution, level 3, is encoded as a special case of thegeneral encoding procedure described above. That is, the entire level 3quantized correction image is treated as a non-null region which isencoded using a predetermined code type. In the preferred embodiment,the predetermined code type is DPCM which is described elsewhere in thisdetailed description. However, it is noted that the lowest resolutionlevel quantized correction image could be divided into null and non-nullregions as will be subsequently described with respect to higherresolution quantized correction image levels and such is considered tobe within the scope and contemplation of the present invention. Also,instead of predetermining a code type such as DPCM, an alternateembodiment of the present invention entails encoding each non-nullregion using different vector quantization code types such as DPCM,DYADS and QUADS, determining the best code type under the circumstances,then transmitting a code identifying the code type ultimately employed.

In the preferred embodiment, the 8×8 pixel blocks are grouped into nulland non-null regions preferably using a binary tree encoding techniquesimilar to that described elsewhere in this detailed description. Themajor difference is that in the binary tree encoding technique employedwith the quantized correction images, the image is split up in a way soas to maximize the number of pixels in null regions, while minimizingthe total number of regions created. In the preferred embodiment, splitsare made only along the borders of the 8×8 pixel blocks and not throughthe blocks. Consequently, a pixel block which contains one or morenon-null pixels would lie entirely within a non-null region. Althoughbinary tree encoding is preferred, other methods of forming regions maybe used such as, for example quad tree decomposition; and such areconsidered to be within the scope of the present invention.

In the example depicted in FIG. 65, the image has been divided intoseven null (N) and non-null (NN) regions of various sizes. Each nullregion N contains only those pixel blocks in which all of the pixelvalues have been quantized to zero. Each non-null region NN includes atleast one pixel block in which there is at least one pixel having anon-zero quantized value.

For purposes of this example, the full resolution image is assumed tocomprise an array of 256 pixels horizontally by 240 pixels vertically.Region 6502 is a rectangle 128 pixels wide and 120 pixels high. Thepixel in the upper left corner of region 6502 occupies location 0,0.Region 6504 is a rectangle which is 128 pixels wide and 64 pixels high.The pixel in the upper left corner of region 6504 is at pixel location128,0. Region 6506 is a rectangle which is 64 pixels wide and 56 pixelshigh. The pixel in the upper left corner of region 6506 is at pixellocation 128,64. Region 6508 is a rectangle which is 64 pixels wide and56 pixels high. The pixel in the upper left corner of region 6508 is atpixel location 192,64. Region 6510 is a rectangle which is 64 pixelswide and 120 pixels high. The pixel in the upper left corner of region6510 is at pixel location 0,120. Region 6512 is a rectangle which is 64pixels wide and 120 pixels high. The pixel in the upper left corner ofregion 6512 is at pixel location 64,120. Region 6514 is a rectanglewhich is 128 pixels wide and 120 pixels high. The pixel in the upperleft corner of region 6514 is at pixel location 128, 120.

It should be noted that for those pixel arrays having dimensions whichare not multiples of 8, the 8×8 pixel blocks along the lower and/orright borders are truncated in the preferred embodiment. For example,assuming the array depicted in FIG. 65 is an array of pixel values forthe luminance component, the array for the subsampled U and V componentswould be 64 ×60 assuming a subsampling factor of 4 in a preferredembodiment. That is, each of the U and V components will have 1/16 asmany pixels in the array as the luminance components array. Since thevertical array dimension of 60 pixels is not an integer multiple of 8,the lower of row of pixel blocks in each of the U and V component arrayswould be truncated to 8×4 pixels each.

In the preferred embodiment, a region table is formed that identifieseach region by the horizontal and vertical position of the pixel in theupper left corner of the region; the height of the region; the width ofthe region; whether the region is a null N or non-null NN region; andthe code types employed for the non-null regions. This region tableinformation is encoded using the binary tree and inserted into the bitstream. An example of a region table which identifies the regionsdepicted in FIG. 65 is shown in FIG. 66. Region 6502 is identified inthe region table as having an upper left pixel location of 0,0; a widthof 128; a height of 120; and it is a null region (N). Region 6506additionally includes an entry indicating DPCM as the code type employedsince region 6506 is a non-null region. The other regions are similarlyidentified in the region table depicted in FIG. 66. It should be notedthat the left column of the region table depicted in FIG. 66 is usedonly for the purposes of this detailed description and is not part ofthe region table formed in accordance with the present invention.Because all of the pixel values in a null region have been quantized tozero, the values of pixels in null regions are implicit. That is, thedecoder will automatically assign a value of zero to each pixel locationin a null region. The non-null regions of each resolution level areencoded using an appropriate code type.

As previously stated, the entire level 3 quantized correction image istreated as a single non-null region and is encoded using the DPCMencoding technique described elsewhere in this detailed description. Thenon-null regions of higher resolution quantized correction images areencoded using appropriate code types. In the preferred embodiment, thenon-null regions of each of the quantized correction images ofresolution levels intermediate the lowest level and full resolution areencoded using the same code type which is preferably the dyad code typedescribed elsewhere in this detailed description.

The non-null regions of the full resolution level zero quantizedcorrection image are encoded using yet another code type, preferablyquads. The quad encoding technique is similar to the dyad encodingtechnique described elsewhere in this detailed description; theprincipal difference being that each quad index number represents fourpixel values instead of two. Each set of four pixel values and itsassociated quad index number is listed in a quad table. The quad tableis inserted into the digital video data stream. Although the preferredembodiment of the present invention utilizes different code types forthe lowest resolution level, the full resolution level and theresolution levels intermediate the lowest and full resolution levels,the same code types can be used for all levels of resolution ordifferent code types could be used for different levels of resolution orfor different regions in each level of resolution and such areconsidered to be within the scope and contemplation of the presentinvention.

FIGS. 39-43 provide details for implementing the inter-frame coder 1620of FIG. 16. As previously mentioned, inter-frame coding is used for thesecond and subsequent frames of a motion video sequence to takeadvantage of correlation or redundancy which exists between frames in atypical motion video sequence. The advantage is that if a region of aprevious frame may be found that corresponds fairly well to a regionbeing coded in a current frame, then one need only code the differencesrather than the absolute values as was done in the intra-frame coder1610. An advantage of inter-frame coding, as previously noted, is thatthe differences values tend to be small numbers that can be encoded withfewer bits. Region motion, due to panning or object movements within ascene, requires an additional code parameter, namely, the offset valuesX_(o) and Y_(o). The offset values X_(o) and Y_(o) represent the amountby which a moving object has translated in the horizontal and verticaldirections between the current and the previous frame.

FIG. 40 illustrates the motion effect. The solid region 4004 representsa particular region of the current frame. Region 4002 is a region in theprevious frame containing picture information corresponding to theinformation in region 4004. Relative to the corresponding region 4002,region 4004 has moved by X_(o) horizontally and Y_(o) vertically. As anoverview, one task of coder 1620 is to encode the region 4004 (hereafterthe "target" region T) as a bi-linear polynomial Ax+By+C representingthe differences between regions 4004 and 4002. The differences in thelocation of the regions X_(o), Y_(o) (hereafter, the "offset") is alsocoded to enable a decoder to locate the previous image and add thedifferences thereto to reconstruct the target image. This form of codingwill hereafter be referred to as "relative" linear fill coding todistinguish it from the "absolute" linear fill coding of coder 1610.Other functions provided by coder 1620 include providing a high speedsearch routine for locating regions "C" in the previous framecorresponding to the target image in the current frame and, providingdefault coding alternatives if a suitable previous region can not befound.

FIG. 39 is a detailed flow chart illustrating each step in theinter-frame coding process provided by coder 1620. This "software"implementation is presently preferred. It will be appreciated that theindividual processing functions may readily be implemented by individualapparatus elements providing the functions shown in the flow chart.Inter-frame coding is initiated (START 3902) by placing mode switch 240'(see FIG. 16) in the down position to begin encoding the second frame ofa motion video sequence. Recall that switch 240' was previously in theUP position for coding the first frame using intra-frame coder 1610.This previous frame is already coded and stored in buffer store 232(FIG. 2) and is also stored in uncoded form for comparison with thecurrent frame to be coded.

Inter-frame encoding is performed separately on the Y, I and Qsubframes. After starting the inter-frame coding, the next step 3904comprises selecting the target (T) and the corresponding (C) previousregions. The target image controls the selection of the correspondingregion by selecting the corresponding region to be of exactly the samesize and, initially, at exactly the same location (X,Y coordinates) inthe previous frame as the target region. As will be explained, a searchis then performed in the vicinity of the target region coordinates tocompensate for frame-to-frame motion effect.

The target region is selected similar to region selection for absolutefill encoding of still frames. Originally the entire image area isselected as the target region. If this region cannot be adequatelyencoded, it is split into sub-regions which are subsequently examinedfor encoding.

Once a target region is selected the resulting processing is the sameregardless of whether the current region is the whole image, or one ofthe regions placed on the region list (3904) by a split action. If aregion is available for processing (3908), it is examined (3910) todetermine whether this region has already undergone motion compensation.If it has, there is no need to repeat this processing, and processingskips directly to step 3930. As will be described in later discussionsof motion compensation, step 3928 generates a code describing therelative displacement of the "T" and "C" regions. This code is includedin the code stream only once for a given region and all sub-regionsderived from it later by splitting. This helps reduce the size of thecoding bit stream and is one of the many benefits of binary treedecomposition.

If step 3910 determines that motion compensation has not yet beenperformed, the motion compensation process 3920 is initiated.

Briefly, the process 3920 comprises searching for a region "C" of theprevious frame which most closely matches the target region "T" of thecurrent frame. If no motion has occurred, regions C and T will have thesame coordinates. If motion has occurred, region C will be offset ortranslated relative to region T by an amount X_(o), Y_(o). The meansquare difference (MSD) between corresponding pixel values of the targetregion and the best choice for the translated "C" region is calculated.This MSD value is compared (3922) against a threshold entered viathreshold control 238 (FIG. 2). If the comparison indicates that thisbest choice for a translated region does not provide an acceptable matchto the target region, the target region is checked for minimum size(3924). If the target region is larger than the minimum size, it issplit (3926) and motion compensation is performed on the split regions.If a translated region is found, which acceptably matches the targetimage (that is, passes test 3922) or the target region is of minimumsize the X_(o) Y_(o) displacement values are encoded (3928) to providethe region offset in the region description code. If step 3928 isreached via step 3924, and has not satisfied test 3922, the translatedregion will not accurately describe the target region. This occurs forexample if the camera is panning and hence there are no antecedentpixels. Subsequent steps in FIG. 39 will represent the region as best asit can, probably via absolute DPCM.

A more detailed discussion of motion compensation will now be presentedwith reference to FIGS. 40, 41, 42 and 43. The purpose of motioncompensation 3920 is to determine the offset or displacement of theregion "C" that most closely approximates the target region. The processshown in FIG. 42 is a directed search for a displacement that minimizessome measure of closeness of fit. Nominally the mean square difference(MSD) between the two regions is used as the closeness of fit measure.The particular target region may contain a large number of pixel valuesand hence evaluating the MSD can be very time consuming. The timerequired to make this calculation may be significantly reduced withoutsignificantly affecting the end result, if the mean square difference iscalculated only for a properly chosen subset of the pixels.

The first step in FIG. 42 is to determine (4210) a representative set ofpixels for the MSD calculation. A strategy of picking the pixels atrandom, but uniformly distributed over the region has proven to beeffective. The number of representative pixels needed in the subsetdepends roughly on the square root of the area of the region. Moreprecisely, the required number is determined from the formula K√A, whereK is a parameter entered via threshold control 238, and typically about10 and A is the region area. In order to assure that the representativepixels are uniformly distributed throughout the region, the region isconsidered to be composed of K!A equal sized sub-regions, and a pixelrandomly selected from each of these sub-regions.

Next, simple low pass filtering is applied to the "T", and "C" regions.Such a filter (4204) makes use of representative pixels less sensitiveto random effects. This filtering operation is done only for motioncompensation, and the filtered regions are discarded before subsequentprocessing of the region.

The first phase of the search begins by setting (4220) the searchresolution to one pixel. While it is desired to know the displacementbetween the target region and a corresponding "C" region to greaterresolution, starting with single pixel resolution has two advantages.First, larger translations can be made with fewer time-consumingevaluations of the MSD. Second, the calculation time for the MSD isfaster. The latter is true because calculating the MSD for fractionaldisplacements of a pixel requires the additional step of interpolationbetween pixels.

Next trial evaluations of the MSD are done in eight different directionsfrom the starting point (4230). These eight possible directions areshown in FIG. 41. The direction that gives the greatest reduction in theMSD is pursued. In practice, it is not necessary to do eight MSDcalculations to pick the best direction. The algorithm assumes that theMSD is roughly a linear function in the neighborhood of the startingpoint. Hence, if the direction L gives a reduction, it is expected thatdirection R will give an increase, and its MSD is not evaluated.Similarly a reduction in the direction U will suppress the evaluationfor the direction D. Finally, it is only necessary to evaluate nediagonal direction; first the best horizontal and vertical directionsare determined, and then the diagonal direction between them isexamined. This strategy often points in the right general direction.Further, even if it points in the wrong direction, other steps in theprocess can eventually direct the search in the proper direction.

Usually when these various directions have been examined, a direction isfound that decreases the MSD more than others. If such a directionexists the test for local minima (4240) will fail, and the searchproceeds to step 4260. At this point "C" regions are examined only alongthe direction which produced the smallest MSD at step 4230. Test regionsare examined, with one pixel resolution, in the chosen direction for aslong as the MSD continues to decreases. This process is suggested by thedouble arrow in FIG. 41. When further translations produce no furtherdecreases of the MSD, step 4230 is repeated to find a new searchdirection. This process continuous until there is not further reductionin the MSD. Then the resolution is increased to one eighth pixel (4240,4250, 4270) and the search process repeats at this higher resolutionuntil there is again to further reduction in MSD and the search ends(3922) with the values of X_(o) Y_(o), being stored for possiblesubsequent encoding 3928.

Pixel values in the "C" regions are only available at one full pixelresolution. Searching for regions in the "C" frame at e.g., 1/8th pixelresolution can only be meaningful if pixel values are available at 1/8thpixel interval resolution. These pixel values are generated byinterpolation to produce values at 1/8 pixel increments. There are manyknown interpolation algorithms which may be used to produce these valuessuch as linear interpolation, quadratic interpolation, cubicinterpolation etc.

FIG. 43 provides further illustration of the process of motioncompensation and relative coding and illustrates the substantial regiondata reduction obtained. In this example the C region 4304 of theprevious frame is assumed to be of uniform brightness (5 units). Thetarget region 4302 is similar but has vertical and horizontal gradientsof -1 and +1 units per pixel. Subtraction (4306) results in a differenceimage, I, 4308 with relatively low valued pixels to encode. As shown,the code comprises the changes in brightness (C) and gradients (A, B)and the region offset code X_(o) Y_(o).

When motion compensation is completed for a target region, processing iscontinued at step 3930. Step 3930 determines the type of encoding to beperformed on the target region. First, a region is generated comprisedof difference values of corresponding pixel values in the target andselected "C" regions (see FIG. 43). If none of the difference values inthis generated region are greater than a threshold, typically 30, thetarget region is classified as relative and selected for relativeencoding. The advantage of relative encoding is that it tends to resultin larger regions with smaller code values, and hence results in smallercode size and decode time. In this case we exit step 3930 along thedecision path labeled relative (REL.).

Returning to FIG. 39, if there are difference values in the generatedregion greater than the threshold, the target region is not classifiedrelative, but it is conceivable that part of it may successfully beprocessed by relative encoding. Hence step 3930 performs a trial split,and examines the two resulting subregions. This trial split uses asimple split (FIG. 35A). If either of these sub-regions satisfies thethreshold requirement step 3930 is exited along the decision pathlabeled mixed, which leads to the split step 3938, so that the two halfsize regions can be separately processed. The split at 3938 is also asimple split.

The split at step 3938 is preceded by a minimum size test (3936). If thesplit at 3938 would reduce the region below the minimum size, theminimum size test (3936) reclassifies the target region as absolute.This prevents the generation of very small planar fill regions, whichare inefficient both in code size and decode time.

It may be that neither half of the trial split region results in asub-region that can clearly be classified as relative. In that casetrial splits are performed (3930) on each of the sub-regions. Thisprocess continues until one of two things results. If a sub-region isfound that is clearly relative step 3930 is exited along the mixeddecision path. Otherwise trial splitting is continued until theresulting regions would fail the minimum region size test. If thishappens, that is, no trial subregion is found which is larger than theminimum size, and is clearly relative, then the region is classified asabsolute and step 3930 is exited along the absolute decision path to3934.

If the exit is along the mixed path, the region will be split by step3938. These sub-regions will eventually each be processed by step 3930again. Since the reason for exiting along the mixed exit was thepresence of a trial region that could be classified as relative, thesplit at 3938 will eventually yield that region.

Once the region has been classified, it is identified by relative andabsolute flags at steps 3932 and 3934 for subsequent use in fillprocessing (steps 3952 and 3968).

It will be noted that relative regions are low-pass filtered at step3929 after encoding of the X_(o) Y_(o) offset values (step 3928) andbefore region classification (step 3930). Filtering at this pointremoves extraneous detail which increases the probability that largerregions will be classified as relative thereby reducing code size anddecode time. The target image is also filtered in case the region isclassified absolute which tends to increase the size of absoluteregions. In this regard it has been found that an additional nonlinearfilter is very helpful. The eye is less sensitive to loss of detail inthe difference value region, since the eye sees the sum of the encodeddifference values and the pixel values in the "C" region. Therefore, itis extremely useful to weight the amount of filtering based on the humanperceptual system. There are two reasons why the eye may be lesssensitive to errors in one part of the difference image than another,and these two reasons are both used to determine the amount of filteringon a pixel by pixel basis. First, those portions of the differenceregion where the target region is bright are filtered more strongly thenthose portions where the target region is dark. Second, those portionsof the difference region where the target region is "busy" (i.e.,detailed) are filtered more strongly than those portions where thetarget region is relatively smooth. That is, if the target region ischanging slowly, errors in the difference region will be more visuallyapparent than if the target region has a lot of detail. The degree ofbusyness of a point is estimated by subtracting neighboring pixelvalues, thereby getting a measure of the local gradient. In view of theforegoing, the detector 3624 in FIG. 36A may be modified to increase thedamping factor D for bright and/or busy images.

The next processing step is to try and represent the region by a planarsurface: Ax+By+C. This step (3952) is either applied to the differenceregion or the target region, depending on whether step 3930 hasclassified the region as relative or absolute. This process isessentially the same as previously described for FIG. 17 steps 1706 to1716.

If the region fails the roughness threshold test 3942, the region willbe tested for minimum size (3964). If the region is greater than minimumsize, a split is done (3966) and new target regions generated forselection (3904). Conversely if the region size falls below a thresholdvalue, one of two techniques is pursued depending on whether the regionhad been classified as absolute or relative. For absolute regions DPCMencoding (3970) of the region is performed which is substantially thesame technique used for intra-frame encoding, and described in thatcontext.

For relative regions, a different technique, referred to as dyadencoding, is implemented. This technique is optimized for regions thatare fairly flat, but have a few exceptional pixels that prevent it frombeing properly encoded as a planar surface. Dyad encoding will bedescribed in reference to FIG. 61. This figure shows a representativeregion of eight pixels in the target region 6110, and the associatedbest match corresponding region 6120 of the previous frame. The encoderwill generate the target image pixels A₁ and B₁ by respectively addingthe pair of values R, S, to the corresponding pixels, C₁ and D₁. Thepair of values R, S, is herein referred to as a dyad. The decoder willfind the pair of values R, S, in a dyad memory table by using the codevalue from the data stream to generate address values for application tothe dyad memory.

FIG. 62 illustrates the dyad coding process. Eleven dyad points (soliddots) are plotted on the diagonals of an RS coordinate system. Thecoordinates of the dyad points are entered in compressor 230 by means ofthreshold control 238. The dyad points are numbered K1-K11 and it is thedyad number (not its coordinate values) which is used to encode a pairof difference values R, S. This may be done by plotting the actual pixeldifference values as a point (P) in the RS plane and choosing thenearest dyad point K as the code value. As an example, in FIG. 61 assumethat pixels A₁ and B₁ are to be encoded. First, C₁ of the previous fieldis subtracted frame A₁ to yield a difference value R₁. Then D₁ issubtracted from B₁ to yield the difference value S₁. For purposes ofillustration assume that R₁ =10 and S₁ =13. These values are then usedas coordinates of point P (10, 13) in FIG. 62 and plotted in the RSplane. As shown, the closest dyad to point P (10, 13) is dyad number K6at coordinates R=14, S=14. One may, therefore, encode A₁ B₁ of region6110 (FIG. 61) by transmitting the dyad designator K6. When decoded (bya table look-up of K6) the A₁ and B₁ pixels would be only slightlybrighter than their original values. Specifically, the true value ofpixel A₁ is C₁ +10 and the true value of pixel B₁ is D₁ +13. Using dyadK6, the decoded values will be C₁ +14 and D₁ +14 which is very close tothe true values of the pixel pair A₁ B₁.

It has been found that a superior dyad decoded image may be obtained bymodifying the foregoing dyad selective procedure. In the example given,the dyad K6 was seen to provide a slightly brighter pixel pair A₁ B₁when decoded than would be the case if the "true" differences had beentransmitted. Accordingly, in the previous example the dyad K5 would be abetter choice for encoding pixel pair P rather than K6 even though thecoding errors are clearly somewhat larger for the given example. Afurther reason for choosing the smaller dyad is that it skews the dyadfrequency distribution towards smaller values thereby allowing thevariable length encoder 1640 to be more efficient.

A further aspect of dyad region-specific coding shown in FIG. 62 is thatthe dyads K1-K11 are not uniformly spaced along the left and rightdiagonals of the pixel difference RS plane. Specifically, dyads near theorigin are more closely spaced than those farther away. The effect isthat there are more dyads available for coding small pixel pairdifference (R, S) and thus the coding accuracy is improved as thedifferences A-C and B-D become smaller. This is important because it hasbeen discovered that the eye is more sensitive to errors in the dyadvalues when the values are small.

It will be readily apparent that the accuracy of dyad encoding may beenhanced by increasing the number of dyads K_(i), For example, dyads maybe determined along two diagonals (e.g., 30° and 60°) rather than alongthe illustrated diagonal along 45°. In general, a number of dyad tablesare available and a table is selected which best fits the region data.The particular table used is indicated as part of the encoded data.

To summarize, step 3904 provides a region for possible encoding by steps3960, 3970 or 3980. If the region is not encoded, it is split at 3926,3938 or 3966, and the separate subregions analyzed for possibleencoding. Eventually the minimum size tests (3924) (3936) and (3964)force every region to be encoded.

Once every region has been encoded, the condition that all regions havebeen encoded is detected (3908). The process then shifts to the remergeoperation (3990). Remerge examines the encoding generated for allregions of the images, and where possible, merges adjacent quad encodedregions, adjacent dyad encoded regions and adjacent DPCM encodedregions. This process is similar to the remerge operation discussed withrespect to step 1720 of FIG. 17.

After remerge (3990) the process checks (3982) for further frames in thesequence. If there are no further frames, then all frames of thesequence have been compressed, and the process of FIG. 39 is exited(3998). If there are more frames, the next frame is readied (3984) forcompression, and the process is repeated.

Returning to FIG. 16, the next compression process after intra-frame andinter-frame coding comprises applying the coded signals S12 and S13 toan area dependent adaptive quantizer 1630. This quantizer, as previouslydescribed, quantizes the coded data as a function of the region area.This quantizer is only applied to the "C" coefficient of the Ax+By+Clinear fills. Area dependent quantization of coefficients A and B hasbeen found to not be necessary because these coefficients are typicallyless than unity. The average brightness "C" of large regions isnominally represented by all eight bits. Smaller regions areprogressively quantized using fewer bits and thus shorter code words.

FIG. 44 is a table listing region sizes and the number of bits used torepresent the region fill value. For a region of 32 pixels or more, 8bits are used, thereby providing a fine resolution of 256 brightnesslevels. For regions in the range of 16 to 31 pixels, seven bits providea resolution of 128 levels. One bit is dropped each time the area ishalved. A one-pixel region is quantized to 3 bits giving a coarseresolution of 18 brightness levels.

From the foregoing, it is seen that 5 bits are saved for each one-pixelregion, 4 bits are saved for each two-pixel region, etc. Area dependentadaptive quantization provides an additional data reduction as comparedwith assigning a full resolution value (8-bit byte) to every region fillvalue. Moreover, variable quantizing has been found to be visuallyacceptable because the large regions which are more visible are finelyquantized thereby giving an overall appearance of high resolution. Thesmaller coarsely quantized regions are, in a manner of speaking,psycho-visually masked by the presence of large high resolution regions.

FIG. 45 is a flow chart implementation of the area dependentquantization of FIG. 44. The process begins by getting the height andwidth data for a region (4502) from a region data memory and computingthe region area 4506. The region area (4506) is tested by area test 4508and 4512 to 4518 to select the corresponding quantizers 4520 to 4528 forprogressively decreasing the number of bits as the region "area"decreases below 32 pixels.

Returning to FIG. 16, the final element of compressor 230 to bedescribed comprises what will herein be denoted as a "stream segmented"variable length code 1640. The term "stream segmented", as used herein,relates to the use of a plurality of variable length codes for eachvideo frame. A minimum of 18 distinct variable length codes aregenerated for every single compressed digital video frame in the exampleherein described.

Recall that variable length codes, as is known, achieve data reductionby assigning shorter codes to more frequently occurring events. It hasbeen discovered that there is no single variable length code that canefficiently code the separately compressed Y, I and Q images. This isbecause the statistics of each of the Y, I and Q subframes aredifferent. Moreover, it has been discovered that there is no singlevariable length code that can efficiently code the separate dataelements of the subframes. Therefore, a different variable length codeis used for each segment of such sub-frame.

Altogether, it has been found that six (6) different variable lengthcodes are effective in describing the markedly different data comprisinga single sub-frame. For this reason, the statistics (i.e., frequency ofoccurrence) of each major data category are calculated for every videoframe stream. Since there are three sub-frames (Y, I, Q) a minimum of 18statistical decoding "tables" are included in every video stream.

FIG. 47 illustrates the data format in detail of a compressed sub-frameof one video stream. The identical format is used for Y, I and Qportions of the compressed video stream.

The "header" segment, as previously mentioned, contains the sub-frametype (Y, I, or Q), its size (i.e., resolution), a check sum, andpointers to three tables (DPCM, dyad and quad) that are used duringdecoding of the sub-frame. The header is followed by code tablesdescribing the specific variable-length codes to be used in decoding theremaining segments of data. For efficiency, these table descriptions arethemselves encoded using an implicit (i.e., agreed upon by the encoderand decoder) code table. The next section contains the binary treedescription, containing "actions" and "values", as previously describedunder "Video Compression Processing". The "relative data" sectionfollows, which contains the coefficients for all the relative bilinearfills. The "absolute data" sections contains only the A, B coefficientsfor absolute bilinear fills, since the C coefficients are contained inthe tree description. The next section contains the DPCM data (one valueper pixel) for all the DPCM regions; the section after that contains the"dyad" data (one value per two pixels) for all the dyad regions; and thelast section contains the "quad" data (one value per four pixels) forall the quad regions. The ordering of the data within each of the lastfour segments is implicit: region data is ordered based on the orderthat regions will be generated by decoding of the binary tree, and pixelbased values (DPCM, dyad and quad) are ordered in ordinary raster-scanorder (top line to bottom line, and left to right within each line).

FIG. 46 is a block diagram of the "stream segmented" variable lengthcoder 1640. The region coded and quantized video signal S14 fromquantizer 1630 is stored in memory 1642 as indicated. A selector switch1644 selects the quad fill data, the dyad fill data, the DPCM fill data,the ABSOLUTE fill data, the RELATIVE fill data and the TREE descriptivedata and the stream HEADER data (source 1646) for application to avariable length coder 1650. Coder 1650 encodes the various types of dataassigning the shortest codes to the more frequently occurring data codewords and stores the variable length coded data in store 1654. Thestored data is selected in the order shown in FIG. 47 to form thecompressed digital video output signal S9 for application to bufferstore 232.

More particularly, variable length encoder 1650 examines each data typeindependently of the other data types, to determine the statistics ofthe data in each data type over the entire subframe. For example, therelative frequency of occurrence of each codeword of the data isascertained along with the range of, e.g. values, of the codewords inthe data set. Using this information, one of a plurality of variablelength code sets is selected which will most efficiently variable lengthencode the respective data types. The plurality of code sets are storedin element 1652. Once a code set is selected, coder 1650 retrieves theselected code set from store 1652 via switch 1644 and proceeds to encodethe corresponding data type.

In addition, the particular variable length code sets are in turnvariable length encoded and added to the data stream to provideadditional data reduction. However, in this case variable lengthencoding is performed using a predetermined (implicit) variable lengthcode set. This feature is provided in FIG. 46 by switch 1644 whichcouples the output of store 1652 to the variable length encoder 1650.

Illustratively, the variable length encoding is a two pass process inwhich code 1650 first generates the code statistics and the variablelength code sets for each of the data types. In the second pass therespective data types in store 1642 and the code sets in statisticsstore 1652 are variable length encoded.

Stream segmentation provides a significant advantage in reducingdecoding time for the compressed video data. This results because itminimizes the number of times the variable length decoder (to bedescribed) must be reprogrammed during decoding to accommodate thedifferent statistics of different code formats. In other words, bygrouping all the DPCM data together the variable length decoder only hasto be programmed once to decode all the DPCM regions. The same advantageresults for the other code formats (relative, absolute, dyad and quad)as well as the tree data and other variable length coded data in FIG.47.

Post Compression Processing

Once a sequence of images has been compressed, the formatter doesfurther processing in preparation for full motion video playback. Thisprocessing is indicated in FIG. 13. In overview, the compressed videodata S10 must be combined with the compressed audio data S8 and anyauxiliary data S3 and prepared for recording on the CD-ROM 18.

The CD-ROM is shown as a representative member of a class of devicesthat have a high storage capacity (more than a 100 megabytes), and arelatively low sustainable data rate (1.23 megabits/sec for the DC-ROM).Other magnetic and optical storage media are also suitable.

FIGS. 8 and 9 illustrate how the audio data S8 is interleaved with thevideo data S10, and with other data to be described. FIG. 8 shows alogical frame. (The adjective logical is used to suggest that a logicalframe may be different from 1/30 of a second, for example in 24 FPSplayback.) in general, a logical frame is the set of all data that areneeded during the time that a single image is displayed. FIG. 8 shows alogical frame which enough video data to construct one image, and enoughaudio data to be generated while the image is displayed. The size of alogical frame is determined by the sustained data rate from the inputdevice (for a CD-ROM, 1.2288 megabits per second), and the imageplayback rate, commonly one every 33.3666 milliseconds. Hence, for 30FPS playback, the logical frame size must average 5125.12 bytes.

FIG. 13 shows how this average rate is achieved. It is a three phaseprocess. In the first phase, data is captured from several sources, andwritten to disk 1350 as an interleaved stream of data. In the second andthird phase, this stream is read back, processed through the ditherswitch 1390 and rerecorded on the disk. As a preview, the first phasecollects the data and performs most of the processing needed to generatea single stream of data S4 that contains interleaved audio and videodata. Phase 2 and 3 deal with any remaining problems, most importantly,with the possibility of oversized frames.

In the first phase, the control unit 1310 directs the audio ditherer1360 to pass a specific amount of audio data each time that switch 1320is coupled to it. The audio dither 1360 addresses the following problem.The audio playback system 32 consumes bits at a specific and welldefined rate. For voice quality audio, this may be set to 31.25kilobits/sec. In order to sustain the maximum possible data rate fromthe CD-ROM player 22, the audio data rate in S16 must precisely matchthis. Too low a data rate from S16 will cause sound processor 32 topause, waiting for data. To high a rate will cause audio data to pile upin the host computer 28, waiting to be played. The audio ditherer 1360assures that the average size of the digital audio data block in FIG. 8is the right size as given by the relationship:

    S·(D+1)/D·T=B

wherein: B is the number of audio bytes per frame, S is the audio datarate, D is the number of audio ADPCM samples between ADPCM resets (e.g.,the ADPCM encoder is reset once for each 256 samples) and T is theperiod (in milliseconds) of the video frame rate. For a frame rate of30FPS, a data rate of 31.25 kilobits per second, reset frequency of 256and a frame period of 33.36 milliseconds, the average value of B isequal to 130.847 bytes per frame.

The audio ditherer 1360 either passes 130 or 134 bytes for each logicalframe. (The block sizes are rounded to multiples of four to increase theefficiency of moving data in the host computer 28). To make thisdecision, ditherer 1360 maintains a running average of how many bytes ithas transferred so far. When the running average is less than 130.847,the audio ditherer 360 passes 134 bytes. When the running average isgreater than 30.847 the audio ditherer passes 130 bytes. The particularvalue 130.847 is passed from control element 1310, and is a function ofthe desired playback rate and the playback audio bit rate.

The switch 1370 is controlled by control element 1310, depending on thenature of the auxiliary data. Some auxiliary data needs to be availableas the motion video is played, and is processed in phase 1. One exampleof auxiliary data may be imbedded directions to the host computer 28 tofade the audio volume at pre-selected times. Other auxiliary data may bepassed via switch 1330, for incorporation in the signal stream duringthe second phase. Such other auxiliary data will not have criticaltiming relationships with the audio or video signal and, thus, may beincluded at convenient locations in the bit stream, i.e., encoded videoframes containing less than the nominal number of bytes. This auxiliarydata may be loaded into the host computer 28 memory, as a side effect ofplaying the motion video sequence.

During Phase 1, for successive logical frames, switch 1320 is switchedsuccessively to the video data S10, the output of the audio ditherer1360, and the output of the switch 1370. Switch 1320 also selects theoutput of a header data source 1361 which describes the length andlocation (pointers) of the individual pieces of data in the logicalframe (FIG. 8). Note, during phase 1 there is no "filler" (i.e.,padding) in the logical frame. Note also, the length of every logicalframe may be different, because compressed video may have differingsizes, because of the audio dithering, and because the amount ofauxiliary data may vary from one logical frame to another. The data forall the logical frames of the sequence are written to the disk store1350, ending phase 1.

When phase 1 is complete, the control element 1310 initiates phase 2. Inthis phase the data collected by phase 1 is read in reverse from thedisk store 1350 and rerecorded via loop 1351 in which switch 1390inserts padding on additional auxiliary data to individual frames of thesequence. This process was earlier referred to as "reverse framesequence reformating."That is, during phase 2 the system e.g., computer,first processes the last frame, then the next to last, etc. The purposeof phase 2 is to generate padding data so that the average size oflogical frame is 5125.12 as shown in FIG. 9 (for 30FPS video).

Consider first the simplest case, the absence of oversize frames. Inthis case, the control unit merely adds the lengths of the audio, videoand auxiliary data it finds, and then inserts enough padding bytes ofzero value to raise the size of the longical frame to 5124 or 5128bytes. The control logic for the dithering switch 1390 works similarlyto that of the audio ditherer 1350. It maintains a running average ofthe size of the logical frame generates so far, and chooses whichever of5124 or 5128 would tend to maintain an average of 5125.12. The requiredsize of this average is set by the control 130, based on the data rateof the recording medium and the desired playback rate in images persecond.

If there are no oversized frames, the padding insertion could have beendone during phase 1. The reason it is done in Phase 2 is to better dealwith oversize frames. FIGS. 10, 11 and 12 illustrate the basic principlebehind the processing of oversize frames. FIG. 10 shows the sizes asequence of logical frames might have at the end of phase 1. Frame 3 isclearly too large to fit in 5125.12 bytes.

FIG. 11 illustrates one possible solution to this problem. On detectionof oversized frames, the formatter sends a signal to the thresholdcontrol 238, requesting that the frame be recompressed harder so that itbecomes small enough to avoid oversize frames. In FIG. 11 the result ofsuch a recompression is shown. To simplify the figure, a logical framesize of 5000 is shown instead of 5125.12.

Note, in general oversize frames cannot be detected until after anentire sequence has been decoded and sent to the formatter. The reasonis that the total size of a logical frame depends on information notdirectly available to the video compressor 30. For example, it may arisefrom the presence of a large block of auxiliary data.

The approach shown in FIG. 12 and implemented in FIG. 13 is a bettersolution, since it does not force recompression of the sequence. If suchadditional compression were done, it is likely that it would result in aperceptible loss of image quality, and the FIG. 12 approach avoids this.The compressed data for each frame should arrive at 1/30 of a secondintervals, but up to a point (to be discussed), it does not matter if itarrives earlier. Hence the data for frame 3 can use space that isnominally associated with frame 2.

In general, the strategy is as follows: Each frame is read starting withthe last and examined. If it fits in the current dithered size for aframe, just enough padding is added (switch 1390) to bring it up to thatsize. If not it is placed in the file so that it will start loadingearly, by borrowing space from the temporally previous frame. Next thetemporally previous frame is examined. Despite the fact that space wasborrowed from it, it is nevertheless possible that it will fit in itsnominal frame allocation. This case is indicate in FIG. 12, where frame2 and frame 3 both fit in the space associated with these two frames. Ingeneral, however, the temporarily previous frame may not fit, even if ititself had not been oversized. In that case it is placed in the file sothat it will be loaded ahead of the frame just processed. In thissituation, no padding is generated, since every byte is needed.Continuing in this way, one of two things can happen. Either these isfound a frame that fits where it was supposed to start, or the processreaches the first frame of the sequence.

In the first case, there is a subsequence of frames whose data can beread off the input device at a steady rate of one per frame. Some of theframes will start loading into the host 28 memory early, but none of theframes arrive late.

In the second case, it is apparently impossible to start the first frameso as to maintain a steady 30 FPS. This problem is solved by a thirdphase. As a result of the second phase processing, the formatter knowshow many extra bytes were generated for the file. In the third phase theformatter reads the file generated by the second phase and generates theS4 bit stream. In this phase, the formatter locks for padding, anddeletes it. This continues until an amount of padding equal to theexcess bytes found in phase 22 has been deleted. The result is a filethat can be played back in real time. In the unlikely case that phase 3fails to find enough padding, the control 1310 signals the thresholdcontrol 238 that the sequence needs to be compressed for less code.

The control 1310 calculates two important statistics during phase 2 and3. First, it may be necessary to preload a certain amount of CD-ROM databefore beginning the playback. Control 1310 calculates this during phase3 by looking at the time when each frame arrives compared to when itshould arrive. Second, when a subsequence in the middle of a sequencehas been blocked together during phase 2, some frames may occur veryearly. The control 1310 can tell exactly when each frame will arrive andhence how much temporary storage is needed for these early frames. Theretwo important statistics are passed to the playback system to controlthe allocation of host computer memory prior to playback. If there isinsufficient host memory, then control 1310 signals the thresholdcontrol that more compression is needed.

The above description ignored switch 1330. When padding is inserted,this basically introduces unused space in the S4 bit stream, that mustbe there to keep new frames arriving at the desired times. Depending onwhat the host computer is doing, there may be auxiliary data that can beloaded as a side effect of playing some motion video. If such data ispresent, control 1310 directs the switches 1370 and 1330 to use thisauxiliary data instead of an equivalent amount of padding.

PLAYBACK SYSTEM

The playback system 8 of FIG. 1 includes a CD-ROM player 22 which playsdisc 20 to provide a recovered audio/video bit-stream signal S15 whichis buffered in CD-ROM controller 24 and supplied to a bus 26 of a "host"computer 28. Recall that "frame header" data of bit-stream S15identifies the location in the bit-stream of the compressed audio data(S7), the compressed video data (S10) and the auxiliary data. Computer28 responds to the frame header identification data for directing theaudio (S16) and video (S17) portions of bit-stream S15 to respectiveaudio (32) and video (30) processors via bus 26. The auxiliary data(S18), if present, is stored in the host computer main memory for use,as an example, in interactive applications of the system.Illustratively, the auxiliary data may comprise address information oflocation on disc 20 of specific still frames or motion video sequences.When prompted to select one of several sequences of still frames, theuser enters his choice by means of input/output device 38 and the hostcomputer responds by sending an appropriate seek command to player 22 bymeans of CD-ROM controller 24.

The sound processor 32 buffers and decodes the audio portion ofbit-stream S15 to continuously supply one or more analog sound signalsS19 to a speaker unit 34. Video processor 30 provides buffering,decoding and interlace conversion of the video portion (S17) ofbit-stream S15. The processed video signal S20 is supplied at 30 framesper second, in for example, 2:1 interlaced RGB component form to adisplay 36 for displaying full motion color video. User interaction(control) of the over-all system is facilitated by an input/output unit38 (e.g., a keyboard, monitor, "joy-stick", "mouse", etc.).

VIDEO DECODING

Video processor 30, illustrated in detail in FIG. 48, decodes each frameof the compressed digital video signal S17 at terminal 4802 to provide afull-motion color video signal S20 (RGB) for display unit 36 (FIG. 1) ininterlaced form at 60 fields per second. Processor 30 includes a timingand control unit 4810 which generates all timing signals for controllingsuch functions as memory read/write operations and decoder selection(switch control) by means of timing and control bus 4812 coupled to thevarious processor elements. To simplify the drawing bus 4812 isindicated only generally by an arrow. Header information relating totiming and control (e.g., frame rate, frame sizes, data pointers, etc.)is supplied to unit 4810 via a header detector 4814 coupled to inputterminal 4802. A multiplex switch 4816 controlled by unit 4810 separatesthe compressed Y, I and Q data (S20) from signal S17 and stores it incompressed form at location 4822 of a video random access memory 4820(outlined in phantom). Switch 4816 also separates the statistical codetable data S22 from signal S17 and applies it to variable length decoder4830. The decoder 4830 decodes the statistical data and stores it in aRAM 4832 for use by a variable length decoder 4830 when the compresseddata S20 is recovered from location 4822 of video RAM 4820

After loading the compressed Y, I and Q data as described above, thedecoding process for one frame begins. To decode one frame, theidentical process is performed three times--once for each sub-frame (Y,I and Q). The following description applies to the decoding of onesub-frame.

The first step in the decompression of one sub-frame is to "parse" thebinary tree description. That is, the tree data, which describes thetree in terms of splits and fills, is converted into an explicit list ofregion locations and sizes and fill types. This is accomplished byapplying the tree data to the tree decoder 4842, which traverses thetree and, at each terminal node of the tree, outputs the relevant datato the region list. This list is stored in the region location table4824 in video RAM 4820.

The general format of the region table is shown in FIG. 49. For eachcell, its "type" (relative, absolute, DPCM, dyad or quad), along withthe coordinates of its upper left corner (X, Y) and its size (H, W) arelisted. If the cell is a relative or a dyad cell, in which case theregion shift interpolator 4858 will be used, the offset values (X_(o),Y_(o),) are also stored. These values specify the relative offsetbetween the region in the current image and its corresponding region inthe previous image. If the cell is absolute, the absolute fill value(which is equivalent to the value C in the fill polynomial Ax+By+C) isalso stored.

FIG. 50 shows an exemplary image and the corresponding region table FIG.51 that would be output by the tree decoder. This image consists of tworegions of each possible type. Notice that all of the cells of aparticular type are not necessarily grouped together in the regiontable, due to the order in which the binary tree is traversed.

Since some types of cells (e.g., dyads) operate on pairs of pixels, itis desirable for all cells to have dimensions (H and W) equal to an evennumber. Simple binary-tree splitting, in which a dimension is divided inhalf on each split, rapidly leads to regions that have odd dimensions,unless the original image dimension are powers of 2. Since this isoverly restrictive, an improved splitting scheme is used, in which adimension D that needs to be split will generate the two values2Int(D/4) and D-2Int(D/4) where Int(D/4) is the integer part of thequotient D/4. This still splits approximately in the middle but ensuresthat all cell dimensions will be even numbers, provided the originalimage dimensions are also even. Since this restriction applies equallyto all three sub-frames, and since the I and Q sub-frames are subsampledby a factor of 4, this means that the overall image dimensions must bemultiples of 8.

FIG. 65 shows an exemplary quantized correction image and thecorresponding region table FIG. 66 that would be output by the treedecoder. As previously stated, the splits in such images are made alongthe borders of 8×8 pixel blocks. Consequently, the splits do notnecessarily divide the split areas into equal halves. Such splits form apart of the binary tree encoding technique of the present invention.

Returning to FIG. 48, video RAM 4820 includes two bit maps, one forstoring pixels of the current frame being decoded (map 4826) and theother (map 4828) storing pixels of the frame that was previously decodedand is available for display on display unit 36 (FIG. 1). To create bitmap 4826 the compressed fill data at location 4822 and the regionlocation data at location 4824 are applied via switches 4850 to aselected one of four decoders 4852, 4854, 4855, 4856 and 4857 dependingon the "type" of fill data i.e. DPCM, absolute, dyad, relative or quad.The fill data at location 4822 is first variable length decoded in unit4830 for application (via switch 4840) to the decoder selector switch4850. Control of switch 4850 is provided by a region fill type detector4851 which directs DPCM fill data to decoder 4852, absolute fill data todecoder 4854, dyad fill data to decoder 4855, quad fill data to decoder4857 and relative fill data to decoder 4856.

The absolute and relative decoders (4854, 4856) receive datarepresenting the region "area" (i.e., the number of pixels in a region)provided by area detector 4853. This is used, as will be explained, in"dequantizing" the fill data which, it will be recalled, is quantized onthe basis of region size for regions having fewer than 32 pixels. Bitmap 4828 receives address data from the dyad and relative decoder 4855and 4856 for supplying region pixel data of the previous frame todecoders 4855 and 4856 via region shift interpolator 4858. As bit map4826 is being generated, bit map 4828 is ready for display on unit 36.This may be facilitated by selecting a video RAM having multipleinput/output ports and buffers. Alternatively, as shown, the contents ofbit map 4828 may be transferred to a separate display buffer 4829 perdisplay purposes.

Since the I and Q data is subsampled by 4:1 both vertically andhorizontally with respect to the Y pixels, an interpolator 4860 isprovided for interpolating the I and Q pixel arrays (64×60 each) back tothe size of the Y array (256×240). The Y, I and Q data is first appliedto a frame repeater 862 which (for 30 FPS playback) doubles the framerate (30 Hz) by reading bit map 4829 twice and interlacing the resultant60 Hz field rate YIQ signal. When 24FPS video is to be displayed at 60fields per second, repeater 4862 repeats decoded frames using a 2-3-2-3repeat sequence. The luminance signal Y and interpolated I and Q signalsare applied to a digital-to-analog (D/A) converter and matrix unit 4804which forms the RGB analog output signal S20 for display unit 36.

FIG. 53 illustrates the process of relative decoding. The value of eachpixel P(x,y) in the current frame 5302 is determined by adding the valueof the polynomial function Ax+By+C to the corresponding pixel P'(x,y) inthe previous frame 5304. The coordinates x and y are measured relativeto the upper left corner of the region. The location of the region 5304in the previous frame is determined by the offset values X_(o) andY_(o), which represent the spatial offset of the region 5304 relative tothe region 5302, expressed in units of 1/8 pixel.

FIG. 54 is a detailed block diagram of relative decoder 4856. The X, Y,H, W, X_(o), and Y_(o) values from region location table 4824 arelatched in latch 5402. The coordinates X, Y are applied to an addresscounter unit 5404 to initialize it to the upper left corner of theregion to be decoded in bit map 4826. The height and width values H, Ware used to specify counter limits horizontally and vertically, so thatthe address counter steps successively through the address of each pixelin the region 5302.

Recall that the X_(o), Y_(o) values represent a region offset expressedin fractional-pixel precision. The integer parts of these values arepassed through the address offset adder 5406 and added to the addressesfrom the address counter 5404. The resulting addresses are applied tobit map 4828 to address the pixels in the previous-frame region 5304.The fractional parts of the X_(o),Y_(o) values are applied to the regionshift interpolator to produce interpolated values at intermediatelocations between the actual pixels in bit map 4828.

The next stage of relative decoder 4856 adds the relative fillpolynomial value Ax+By+C to the shifted region data and stores the newregion 5302 in bit map 4826. The coefficients A, B, and C are read fromthe bitstream and applied to the dequantizer 5472 to undo the area-basedvalue quantization described previously. After dequantization, thecoefficients are applied to to the fill logic unit 5470. This unit takesthe three coefficients and the values of x and y from the addresscounter 5404 and outputs the three terms of the fill polynomial. The xand y values are the region coordinates which are used in logic 5470 todetermine the terms of the fill value. The three resulting terms arethen summed, using adders 5460, 5462, and 5464, with the previous regiondata, and stored in bit map 4826. Recall that the coefficients WA and WBare fractional numbers, and therefore that the fill value output by theadders of FIG. 54 is also fractional. Before writing this value to bitmap 4826, it is truncated twice to an integer once for horizontal andonce for vertical.

FIG. 55 illustrates the decoding of an absolute region. In this casethere is no previous region to consider. The value of the each pixelP(x,y) is the value of the polynomial Ax+By+C, where x and y arecoordinates measured relative to the upper left corner of the region.Recall that the value of C is stored in the region location table, sinceit was encoded with the tree description, but the values of A and B arecontained in the "absolute fill" segment of the bitstream.

FIG. 56 is a block diagram of the absolute decoder 4854. It is similarto relative decoder 4856 but does not use a previous bit map or theregion interpolator. The A, B, and C values are dequantized bydequantizer 5672, as required, and processed by the fill logic 5606 toproduce the terms of the fill polynomial. These terms are added by theadders and the result, after truncating to an integer twice (once forhorizontal and once for vertical), is written to bit map 4826. Theaddress counters 5604 control this process to produce pixel values atall locations within the rectangular region defined by X, Y, H, W.

FIG. 57 illustrates the process of DPCM decoding. A pixel value (P') inregion 5702 is obtained by adding a difference value D to the value ofthe pixel immediately to its left (P). A pixel (such as Q' in thefigure) which is on the left edge of the region, and so does not have aregion pixel immediately to its left, is decoded by adding the value Dto the pixel above it (Q). The pixel in the upper left corner of theregion, which does not have a pixel above it nor a pixel to its left, isdecoded by adding the value D to the constant 128. Recall that all the Dvalues are contained in the DPCM segment of the bitstream.

FIG. 58 is a block diagram of DPCM decoder 4852. The X, Y, H, and Wvalues from table 4824 are stored in latch 5802 and used by the addresscontroller 5804 to generate pixel addresses for every pixel in theregion 5702 being constructed. Controller 5804 also generates pixeladdresses for reading from bit map 4826 to provide the pixels P to beadded with difference values D. The DPCM data from variable lengthdecoder 4830 (FIG. 48) is applied to the DPCM dequantizer 5808, ifrequired, which yields the difference values D. These values are thenadded, using adder 5805, to pixels values read from bit map 4826 (or to128 if it is the first pixel of the region) to produce the new pixelvalue for writing to region 5702 of the bit map 4826.

FIG. 61 illustrates the process of decoding a dyad region. The values ofpixels in the current frame 6110 are determined by adding pairs ofvalues (R, S) to pairs of pixels (C, D) in a corresponding region of theprevious frame 6120 to produce pairs of pixels (A, B) in the currentframe. As in a relative fill region, the location of the region 6120 inthe previous frame is determined by offset values X_(o), and Y_(o),which represent the spatial offset of the region 6120 relative to theregion 6110, in fractional-pixel units.

FIG. 63 is a detailed block diagram of relative decoder 4855. The X, Y,H, W, X_(o), and Y_(o) values from region location table 4824 arelatched in latch 6330. The coordinates X,Y are applied to an addresscounter unit 6332 to initialize it to the upper left corner of theregion to be decoded. The H,W values are used to determine the number ofpixels that will be counted horizontally and vertically by the addresscounter.

The X_(o), Y_(o), values are applied to the address offset adder 6334 togenerate the integer and fractional offset addresses for bit map 4828and interpolator 4858 respectively. To produce pixel values for thetarget region, the shifted region data C,D is read from bit map 4828,processed through the region shift interpolator, 4858, and added to thedyad values R,S using adders 6350 and 6352. The resulting values A,B arewritten to bitmap 4826.

The dyad values are produced by first variable-length decoding a valuefrom the bitstream using decoder 4830, and applying it to the tableaddress generator 6310 to point at a dyad in dyad memory 6320. Forexample, if the value after variable-length decoding is a 3, this wouldcause dyad pair #3 to be read out of the dyad memory.

In decoding a selected image, a correction image having multiple levelsof resolution is formed by decoding the multiple levels of quantizedcorrection images which were encoded and inserted into the bit streamportion of the video sequence data stream as previously described. In apreferred embodiment, depicted in FIG. 67, a level 3 correction image6702 is formed by decoding (6704) the encoded level 3 quantizedcorrection image. A level 2 correction image 6706 is formed by decoding(6708) the encoded level 2 quantized image. A level 1 correction image6710 is formed by decoding (6712) the encoded level 1 quantizedcorrection image; and a level 0 correction image 6714 is formed bydecoding (6716) the encoded level 0 quantized correction image.

In the preferred embodiment, the decoder reconstructs the region tablesusing the decoded binary tree description data. The region tables arethen used, in conjunction with the region fill data, to construct aquantized correction image at each resolution level. Although thecorrection images are preferably constructed using the reconstructedregion tables, they could be constructed directly from the decodedbinary tree description data in conjunction with the region fill data,and such is considered within the scope of the present invention.

The decoder decodes each of the quantized correction images inaccordance with the encoding type specified in the bitstream for thatlevel. For example, as previously described, the entire image area ofthe correction image having the lowest level of resolution (level 3) isencoded, in the preferred embodiment, as a single non-null region, usingthe DPCM encoding technique described elsewhere in this detaileddescription. Accordingly, the compressed fill data for the level 3correction image is applied to the DPCM decoder 4852 (see FIG. 48). TheDPCM decoder 485 then decodes the DPCM data to form the differencevalues D of the pixels comprising the level 3 correction image 6702.

The non-null regions of the level 0 quantized correction image areencoded using the quad encoding technique as previously described.Accordingly, the region location data and compressed fill data for thelevel 0 correction image is applied to the quad decoder 4857 (see FIG.48). The quad decoder 4857 decodes the quad data to form the differencevalues D of the pixels comprising the non-null regions of the level 0correction image 6714. The pixel locations in the null regions, whichconstitute the remainder of the full resolution level 0 correction image6714, are filled with zeros.

As previously stated, the non-null regions of the level 2 quantizedcorrection image are encoded using the dyad encoding technique asdescribed elsewhere in this detailed description. Accordingly, theregion location data and compressed fill data for the level 2 correctionimage is applied to the dyad decoder 4855 which decodes the dyad data toform the difference values D of the pixels comprising the non-nullregions of the level 2 correction image 6706 The pixel locations of thenull regions, which constitute the remainder of the level 2 correctionimage, are filled with zeros. Since, in the preferred embodiment, thenon-null regions of the level 1 quantized correction image are alsoencoded using the dyad encoding technique, the level 1 correction imageis decoded in accordance with the procedure described for decoding thelevel 2 correction image.

In the general case of the present invention, a result image for eachresolution level is formed by adding the difference values D of thecorrection image of that resolution level to the pixel values of areference image having the same level of resolution. In the preferredembodiment depicted in FIG. 67, a level 3 result image 6718 is formed byadding the difference values D of the level 3 correction image 6702 to alevel 3 reference image 6720 comprising an array of pixels all havingthe same value which, in the preferred embodiment, is 128.

The level 3 result image 6718 is expanded to form an expanded level 3result image 6722 The vacant pixel locations created by the expansionare filled by pixels whose values are determined by calculation. In thepreferred embodiment, such pixel values are determined by linearinterpolation which is accomplished by adding the values of the pixelson either side of the vacant pixel location, dividing the resultant sumby 2, then inserting the result in that vacant pixel location. Theexpanded level 3 result image 6722 serves as a level 2 reference imageas described below.

A level 2 result image 6724 is formed by adding the difference values Dof the level 2 correction image 6706 to the corresponding pixel valuesof a level 2 reference image which, in the preferred embodiment, is theexpanded level 3 result image 6722. The level 2 result image 6724 isexpanded to form an expanded level 2 result image 6726. The vacant pixellocations in the expanded level 2 result image 6726 are filled aspreviously described with respect to the expansion of the level 3 resultimage 6718.

A level 1 result image 6728 is formed by adding the difference values Dof the level 1 correction image 6710 to a level 1 reference image which,in the preferred embodiment, is the expanded level 2 result image 6726.The level 1 result image 6728 is expanded to form an expanded level 1result image 6730. The vacant pixel locations in the expanded level 1result image 6730 are filled as previously described with respect to theexpansion of the level 3 result image 6718. A full resolution finalimage 6732 is formed by adding the difference values D of the level 0correction image 6714 to a level 0 reference image which, in thepreferred embodiment, is the expanded level 1 result image 6730. Thefinal image 6732 is stored in memory for subsequent display.

At this point it should be noted that, as previously stated, the fullresolution level 0 quantized correction image is not formed, encoded andtransmitted in the bitstream in the alternate preferred embodiment ofthe present invention. Accordingly, the result image, expanded from thenext lower level of resolution, will form the final image in thisalternative preferred embodiment. Also, since level 2 may be the lowestlevel of resolution in this preferred embodiment, decoding of a level 3correction image is not required and the level 2 reference imagecomprises an array of pixels all having the same value as previouslydescribed with respect to the level 3 reference image 6720.

FIG. 59 is a table listing quantization values for regions smaller than32 pixels. Recall that a one-pixel region was quantized to a resolutionof 3-bits representing 8 levels of brightness. As the area doubles onemore bit of accuracy is used up to full video resolution of 8 bits perpixel. This reduces the number of bits needed to represent smallregions. Decoding or "dequantizing" of this data requires a shift leftto give the bits their proper binary significance when the fill valuesare calculated.

FIG. 60 is a block diagram for implementing the leftshift "dequantizer"operation of FIG. 59. The region height (H) and width (W) data fromregion location table 482 is latched in latches 6002 and 6004 andmultiplied by multiplier 6006 of area detector 4853 (outlined inphantom). The multiplier provides address codes to an area look-up table6008 to obtain shift values as a function of area (FIG. 59). Thesevalues are applied to bit shifter 6010. Quantized variable length filldata to be left justified is applied to the data input of the bitshifter 6010 which left shifts the data in accordance with the shiftvalue provided by table 6008.

The discussion of the decode time monitor 236 indicated that occasionallong-decode images were acceptable, since it is possible to borrowdecode time from the previous image. This notion is discussed further inthe context of FIG. 52 which shows further detail of the video RAM 4820.This memory includes a number of display buffers including a buffer 4826into which the frame currently being decoded is stored, a buffer 4828for storing a frame which was previously decoded, a graphics buffer5202, a pipeline buffer 5204 and a display buffer 4829. Each of thesebuffers is large enough to hold an entire decompressed image. Asdescribed earlier, the decoding process uses data from a previous imagestored in bitmap 4828 to decode the next image or current image which isstored in bitmap 4826. In FIG. 52, the frame contained in buffer 5202was decoded just prior to the frame contained in display buffer 4828 andthe frame contained in display buffer 4829 was decoded just prior to theframe contained in bit map 5204, and so on. That is, the image beingdisplayed from buffer 4829 is not necessarily the image being used bythe decode process, but may in fact have been decoded several frametimes ago.

An advantage of having multiple display buffers is that it permits thehost software to draw graphics on the display before it is viewed. Suchchanges cannot be made on bit map 4826 because it is in the process ofbeing decoded. They cannot be drawn in bit map 4828 since the pixels of4828 are used during decoding, and this cannot be corrupted by graphicspixels. They should not be drawn in buffer 4829 since the drawingprocess would be visible on display 36. Drawing them in buffer 5202 hasnone of these problems.

Another reason for multiple display buffers is that it facilitatesdecode time borrowing. By having a few extra buffers in the video RAM,the time at which a buffer is chosen for display may be independent ofor asynchronous with the decoding process. As long as the pipeline ofimages does not run dry, frame repeater 4862 can work with no visiblepauses or blanks in the displayed image. This principle is similar tothe dithering boxes in FIG. 13. Repeater 4862 maintains a runningaverage of the rate of display of images, and holds the current image oradvances to the next, so as to keep the running average close to thedesired playback rate. This feature is particularly useful forvariable-speed playback applications. For example, a user may wish toslow down or stop the playback frame rate of material recorded at 30 FPSfor viewing details of a particular frame or frame sequence. If 30 FPSrecorded video is to be viewed as a sequence of still frames, then theCD-ROM player may be paused and the contents of the buffer pipeline maybe selectively displayed a frame at a time. The CD-ROM may be operatedin a start-stop mode to keep the display pipeline from emptying.

The formatter 250 (FIG. 2) is designed to assure that the pipeline ofdisplay buffers does not run dry. Based on the values produced by thedecode time monitor 236, it can simulate the behavior of the displaybuffer pipeline during playback, and determine a minimum encoded framesize that prevents pipeline exhaustion. If this value is larger than thememory available on the host for display buffers, control 1310 may beused to signal the threshold control 238 that the compression is to berepeated using higher threshold values so as to obtain shorter decodetimes.

In the examples of the system herein described, a CD-ROM was used as thetransmission media for the compressed signal. Alternatively, othertransmission media may be used such as digital magnetic disk or tape.Also full-sized (e.g., 12 inch) optical discs or discs of the capacitivestorage type may be used for transmission. Transmission of thecompressed signal may also be provided by other means such as satelliteor cable transmission systems. It will further be noted that linear filldata for absolute and relative regions are both represented bycoefficients A, B, C of the equation Ax+By+C. It is to be rememberedthat the coefficients of absolute fill data are related to actual pixelvalues while the coefficients for relative fill data are related to thedifference values between pixels in the target region and pixels in thecorresponding region of the previous frame.

What is claimed is:
 1. A method of encoding a digital motion videosignal comprising the steps of:a--selecting at least one frame from asequence of frames of said digital motion video signal; b--resolvingeach selected frame into at least one lower level of resolution;c--encoding at least one lower resolution level of each of said selectedframes; and d--encoding each non-selected frame of said digital motionvideo signal using only the full resolution level.
 2. The method inaccordance with claim 1 wherein step c comprises encoding at least onelower resolution level but not encoding the full resolution level ofeach of said selected frames.
 3. The method in accordance with claim 1in which step c comprises, for each level of resolution of said selectedframe which is encoded, the steps of:i--forming a correction imagecomprising an array of pixel values, by subtracting pixel values in areference image from corresponding pixel values in that level ofresolution of said selected frame; ii--quantizing the pixel values insaid correction image to form a quantized correction image; andiii--encoding said quantized correction image.
 4. The method inaccordance with claim 3 in which step i for the lowest level ofresolution of said selected frame includes the step of providing areference frame comprising an array of pixels all of which have the samevalue.
 5. The method in accordance with claim 4 in which step i for eachlevel of resolution higher than the lowest level of resolution of saidselected frame includes the steps of:(1) forming a result image having alower level of resolution by adding the pixel values of the quantizedcorrection image at that lower level of resolution to the pixel valuesof the reference image at that lower level of resolution; and (2)forming the reference image at the higher level of resolution byexpanding the result image formed in step (1) to said higher level ofresolution.
 6. The method in accordance with claim 3 wherein step iiicomprises the steps of dividing said quantized correction image intoregions and generating region parameters descriptive of the position,size and fill data for each region.
 7. The method in accordance withclaim 6 wherein the step of dividing said quantized correction imageinto regions comprises dividing said image into null and non-nullregions or into null and linear fill regions.
 8. The method inaccordance with claim 7 wherein said region descriptions are encodedusing binary tree decomposition.
 9. The method in accordance with claim8 in which said non-null regions are encoded using vector quantizationor discrete cosine transform techniques.
 10. The method in accordancewith claim 9 wherein encoding using vector quantization comprisesencoding using DYADS, QUADS, or DPCM.
 11. The method in accordance withclaim 1 in which step d comprises the steps of:i--dividing eachnon-selected frame into regions and generating region parametersdescriptive of the location and size of respective regions within saidframe; ii--for non-selected still frames or a first frame of a sequenceof non-selected frames:(1) determining absolute fill data describingrespective regions; (2) determining DPCM fill data describing respectiveregions for which absolute fill data cannot be determined; (3) variablelength encoding said absolute fill data, said DPCM fill data andcorresponding region descriptive parameters; (4) determining an estimateof decompression time from said variable length encoded absolute, DPCMfill data and corresponding region descriptive parameters; (5) providingsaid variable length encoded fill data and corresponding regionparameters if said estimate is less than a predetermined value, and ifnot, repeating steps (i) and (1)-(5) using a different tolerance indetermining said absolute fill data; and iii--for a succession ofnon-selected frames:(1) comparing pixel values in each region withcorresponding pixel values in a like sized region from a previouslyoccurring frame to develop respective pixel differences; (2) determiningrelative fill data descriptive of pixel differences for respectiveregions; (3) determining DYAD fill data for respective regions in whichrelative fill data cannot be determined; (4) determining DPCM fill datafor respective regions in which relative fill data cannot be determinedand for which DYAD fill data cannot be determined; and (5) variablelength coding said relative fill data, said DYAD fill data, said DPCMfill data and corresponding region parameters.
 12. The method inaccordance with claim 1 wherein step c comprises the stepsof:i--dividing each resolution level which is en coded into null andnon-null regions; ii--encoding said regions using binary treedecomposition; iii--determining vector values describing the pixelvalues in said non-null regions; and iv--quantizing said vector values.13. The method in accordance with claim 12 wherein said vector valuesinclude DYADS, QUADS and DPCM.
 14. The method in accordance with claim 1wherein step a comprises the steps of:i--forming a motion compensateddifference image for each frame of said digital motion video signal;ii--determining the value of a selected parameter associated with saidmotion compensated difference image; iii--selecting a threshold value ofsaid selected parameter; and iv--selecting those frames from thesequence of frames having parameter values which exceed saidpredetermined thresholds.
 15. A method of encoding a digital motionvideo signal comprising the steps of:a--selecting at least one framefrom a sequence of frames of said digital motion video signal;b--encoding each selected frame as a still image including the stepsof:(1) resolving each selected frame into at least one lower level ofresolution; and (2) encoding at least one of the lower levels ofresolution but not encoding the full resolution level; and c--encodingeach non-selected frame of said digital motion video signal using atleast the full level of resolution.
 16. The method in accordance withclaim 15 in which step b(2) comprises, for each level of resolution ofsaid selected frame which is encoded, the steps of:i--forming acorrection image comprising an array of pixels, by subtracting pixelvalues in a reference image from corresponding pixel values in thatlevel of resolution of said selected frame; ii--quantizing the pixelvalues in said correction image to form a quantized correction image;and iii--encoding said quantized correction image.
 17. The method inaccordance with claim 16 in which step i for the lowest level ofresolution of said selected frame includes the step of providing areference frame comprising an array of pixels all of which have the samevalue.
 18. The method in accordance with claim 17 in which step i foreach level of resolution higher than the lowest level of resolution ofsaid selected frame includes the steps of:(1) forming a result imagehaving a lower level of resolution by adding the pixel values of thequantized correction image at that lower level of resolution to thepixel values of the reference image at that lower level of resolution;and (2) forming the reference image at the higher level of resolution byexpanding the result image formed in step (1) to said higher level ofresolution.
 19. The method in accordance with claim 16 wherein step iiicomprises the steps of dividing said quantized correction image intoregions and generating region parameters descriptive of the position,size and fill data for each region.
 20. The method in accordance withclaim 19 wherein the step of dividing said quantized correction imageinto regions comprises dividing said image into null and non-nullregions or into null and linear fill regions.
 21. The method inaccordance with claim 18 wherein said region descriptions are encodedusing binary tree decomposition.
 22. The method in accordance with claim19 in which said non-null regions are encoded using vector quantizationor discrete cosine transform technique.
 23. The method in accordancewith claim 22 wherein encoding using vector quantization comprisesencoding using DYADS, QUADS, or DPCM.
 24. The method in accordance withclaim 15 in which step c comprises the steps of:i--dividing eachnon-selected frame into regions and generating region parametersdescriptive of the location and size of respective regions within saidframe; ii--for non-selected still frames or a first frame of a sequenceof non-selected frames:(1) determining absolute fill data describingrespective regions; (2) determining DPCM fill data describing respectiveregions for which absolute fill data cannot be determined; (3) variablelength encoding said absolute fill data, said DPCM fill data andcorresponding region descriptive parameters; (4) determining an estimateof decompression time from said variable length encoded absolute, DPCMfill data and corresponding region descriptive parameters; (5) providingsaid variable length encoded fill data and corresponding regionparameters if said estimate is less than a predetermined value, and ifnot, repeating steps (i) and (1)-(5) using a different tolerance indetermining said absolute fill data; and iii--for a succession ofnon-selected frames:(1) comparing pixel values in each region withcorresponding pixel values in a like sized region from a previouslyoccurring frame to develop respective pixel differences; (2) determiningrelative fill data descriptive of pixel differences for respectiveregions; (3) determining DYAD fill data for respective regions in whichrelative fill data cannot be determined; (4) determining DPCM fill datafor respective regions in which relative fill data cannot be determinedand for which DYAD fill data cannot be determined; and (5) variablelength coding said relative fill data, said DYAD fill data, said DPCMfill data and corresponding region parameters.
 25. The method inaccordance with claim 15 wherein step b(2) comprises the stepsof:i--dividing each resolution level which is encoded into null andnon-null regions; ii--encoding said regions using binary treedecomposition; iii--determining vector values describing the pixelvalues in said non-null regions; and iv--quantizing said vector values.26. The method of claim 25 wherein said vector values include DYADS,QUADS and DPCM.
 27. The method of claim 15 wherein step a comprises thesteps of:i--forming a motion compensated difference image for each frameof said digital motion video signal; ii--determining the value of aselected parameter associated with said motion compensated differenceimage; iii--selecting a threshold value of said selected parameter; andiv--selecting those frames from the sequence of frames having parametervalues which exceed said predetermined thresholds.
 28. An apparatus forencoding a digital motion video signal comprising:a--means for selectingat least one frame from a sequence of frames of said digital motionvideo signal; b--means for resolving each selected frame into at leastone lower level of resolution; c--means for encoding at least one lowerresolution level of each of said selected frames; and d--means forencoding each non-selected frame of said digital motion video signalusing only the full resolution level.
 29. A method of decoding a digitalmotion video signal in which at least one selected frame from a sequenceof frames has been resolved into at least one lower level of resolutionwhich is then encoded, and in which each non-selected frame has beenencoded at the full resolution level only, said method comprising thesteps of:a--decoding each level of resolution of each selected frame toform a correction image comprising an array of pixel values having thatlevel of resolution; b--forming a result image at each level ofresolution by adding the pixel values in a reference image having thatlevel of resolution to the pixel values of the expansion of thecorrection image to the same level of resolution; and c--decoding saidnon-selected frames.
 30. An apparatus for decoding a digital motionvideo signal comprising:a--means for applying a digital motion videosignal in which at least one selected frame from a sequence of frameshas been resolved into at least one lower level of resolution which isthen encoded, and in which each non-selected frame has been encoded atthe " full resolution level only; b--means for decoding each level ofresolution of each selected frame to form a correction image comprisingan array of pixel values having that level of resolution; c--means forforming a result image at each level of resolution by adding the pixelvalues in a reference image having that level of resolution to the pixelvalues of the expansion of the correction image to the same level ofresolution; and d--means for decoding said non-selected frames.